pysam: htslib interface for python

Author:Andreas Heger, Kevin Jacobs and contributors
Date:Jun 18, 2017
Version:0.11.2.2

Pysam is a python module for reading, manipulating and writing genomic data sets.

Pysam is a wrapper of the htslib C-API and provides facilities to read and write SAM/BAM/VCF/BCF/BED/GFF/GTF/FASTA/FASTQ files as well as access to the command line functionality of the samtools and bcftools packages. The module supports compression and random access through indexing.

This module provides a low-level wrapper around the htslib C-API as using cython and a high-level, pythonic API for convenient access to the data within genomic file formats.

The current version wraps htslib-1.3, samtools-1.3 and bcftools-1.3.

To install the latest release, type:

pip install pysam

See the Installation notes for details.

Contents

pysam - An interface for reading and writing SAM files

Introduction

Pysam is a python module that makes it easy to read and manipulate mapped short read sequence data stored in SAM/BAM files. It is a lightweight wrapper of the htslib C-API.

This page provides a quick introduction in using pysam followed by the API. See Working with BAM/CRAM/SAM-formatted files for more detailed usage instructions.

To use the module to read a file in BAM format, create a AlignmentFile object:

import pysam
samfile = pysam.AlignmentFile("ex1.bam", "rb")

Once a file is opened you can iterate over all of the read mapping to a specified region using fetch(). Each iteration returns a AlignedSegment object which represents a single read along with its fields and optional tags:

for read in samfile.fetch('chr1', 100, 120):
     print read

samfile.close()

To give:

EAS56_57:6:190:289:82       0       99      <<<7<<<;<<<<<<<<8;;<7;4<;<;;;;;94<;     69      CTCAAGGTTGTTGCAAGGGGGTCTATGTGAACAAA     0       192     1
EAS56_57:6:190:289:82       0       99      <<<<<<;<<<<<<<<<<;<<;<<<<;8<6;9;;2;     137     AGGGGTGCAGAGCCGAGTCACGGGGTTGCCAGCAC     73      64      1
EAS51_64:3:190:727:308      0       102     <<<<<<<<<<<<<<<<<<<<<<<<<<<::<<<844     99      GGTGCAGAGCCGAGTCACGGGGTTGCCAGCACAGG     99      18      1
...

You can also write to a AlignmentFile:

import pysam
samfile = pysam.AlignmentFile("ex1.bam", "rb")
pairedreads = pysam.AlignmentFile("allpaired.bam", "wb", template=samfile)
for read in samfile.fetch():
     if read.is_paired:
             pairedreads.write(read)

pairedreads.close()
samfile.close()

An alternative way of accessing the data in a SAM file is by iterating over each base of a specified region using the pileup() method. Each iteration returns a PileupColumn which represents all the reads in the SAM file that map to a single base in the reference sequence. The list of reads are represented as PileupRead objects in the PileupColumn.pileups property:

import pysam
samfile = pysam.AlignmentFile("ex1.bam", "rb" )
for pileupcolumn in samfile.pileup("chr1", 100, 120):
    print ("\ncoverage at base %s = %s" %
           (pileupcolumn.pos, pileupcolumn.n))
    for pileupread in pileupcolumn.pileups:
        if not pileupread.is_del and not pileupread.is_refskip:
            # query position is None if is_del or is_refskip is set.
            print ('\tbase in read %s = %s' %
                  (pileupread.alignment.query_name,
                   pileupread.alignment.query_sequence[pileupread.query_position]))

samfile.close()

The above code outputs:

coverage at base 99 = 1
    base in read EAS56_57:6:190:289:82 = A

coverage at base 100 = 1
    base in read EAS56_57:6:190:289:82 = G

coverage at base 101 = 1
    base in read EAS56_57:6:190:289:82 = G

coverage at base 102 = 2
    base in read EAS56_57:6:190:289:82 = G
    base in read EAS51_64:3:190:727:308 = G
...

Commands available in csamtools are available as simple function calls. For example:

pysam.sort("-o", "output.bam", "ex1.bam")

corresponds to the command line:

samtools sort -o output.bam ex1.bam

Analogous to AlignmentFile, a TabixFile allows fast random access to compressed and tabix indexed tab-separated file formats with genomic data:

import pysam
tabixfile = pysam.TabixFile("example.gtf.gz")

for gtf in tabixfile.fetch("chr1", 1000, 2000):
    print (gtf.contig, gtf.start, gtf.end, gtf.gene_id)

TabixFile implements lazy parsing in order to iterate over large tables efficiently.

More detailed usage instructions is at Working with BAM/CRAM/SAM-formatted files.

Note

Coordinates in pysam are always 0-based (following the python convention). SAM text files use 1-based coordinates.

Note

The above examples can be run in the tests directory of the
installation directory. Type ‘make’ before running them.

See also

https://github.com/pysam-developers/pysam

The pysam code repository, containing source code and download instructions

http://pysam.readthedocs.org/en/latest/

The pysam website containing documentation

API

SAM/BAM files

Objects of type AlignmentFile allow working with BAM/SAM formatted files.

class pysam.AlignmentFile

AlignmentFile(filepath_or_object, mode=None, template=None, reference_names=None, reference_lengths=None, text=NULL, header=None, add_sq_text=False, check_header=True, check_sq=True, reference_filename=None, filename=None, duplicate_filehandle=True, ignore_truncation=False)

A SAM/BAM/CRAM formatted file.

If filepath_or_object is a string, the file is automatically opened. If filepath_or_object is a python File object, the already opened file will be used.

If the file is opened for reading an index for a BAM file exists (.bai), it will be opened automatically. Without an index random access via fetch() and pileup() is disabled.

For writing, the header of a SAM file/BAM file can be constituted from several sources (see also the samtools format specification):

  1. If template is given, the header is copied from a another AlignmentFile (template must be a AlignmentFile).
  2. If header is given, the header is built from a multi-level dictionary.
  3. If text is given, new header text is copied from raw text.
  4. The names (reference_names) and lengths (reference_lengths) are supplied directly as lists.

When reading or writing a CRAM file, the filename of a FASTA-formatted reference can be specified with reference_filename.

By default, if a file is opened in mode ‘r’, it is checked for a valid header (check_header = True) and a definition of chromosome names (check_sq = True).

Parameters:
  • mode (string) –

    mode should be r for reading or w for writing. The default is text mode (SAM). For binary (BAM) I/O you should append b for compressed or u for uncompressed BAM output. Use h to output header information in text (TAM) mode. Use c for CRAM formatted files.

    If b is present, it must immediately follow r or w. Valid modes are r, w, wh, rb, wb, wbu, wb0, rc and wc. For instance, to open a BAM formatted file for reading, type:

    f = pysam.AlignmentFile('ex1.bam','rb')

    If mode is not specified, the method will try to auto-detect in the order ‘rb’, ‘r’, thus both the following should work:

    f1 = pysam.AlignmentFile('ex1.bam')
f2 = pysam.AlignmentFile('ex1.sam')
  • template (AlignmentFile) – when writing, copy header frem template.
  • header (dict) – when writing, build header from a multi-level dictionary. The first level are the four types (‘HD’, ‘SQ’, ...). The second level are a list of lines, with each line being a list of tag-value pairs. The header is constructed first from all the defined fields, followed by user tags in alphabetical order.
  • text (string) – when writing, use the string provided as the header
  • reference_names (list) – see reference_lengths
  • reference_lengths (list) – when writing or opening a SAM file without header build header from list of chromosome names and lengths. By default, ‘SQ’ and ‘LN’ tags will be added to the header text. This option can be changed by unsetting the flag add_sq_text.
  • add_sq_text (bool) – do not add ‘SQ’ and ‘LN’ tags to header. This option permits construction SAM formatted files without a header.
  • add_sam_header (bool) – when outputting SAM the default is to output a header. This is equivalent to opening the file in ‘wh’ mode. If this option is set to False, no header will be output. To read such a file, set check_header=False.
  • check_header (bool) – obsolete: when reading a SAM file, check if header is present (default=True)
  • check_sq (bool) – when reading, check if SQ entries are present in header (default=True)
  • reference_filename (string) – Path to a FASTA-formatted reference file. Valid only for CRAM files. When reading a CRAM file, this overrides both $REF_PATH and the URL specified in the header (UR tag), which are normally used to find the reference.
  • filename (string) – Alternative to filepath_or_object. Filename of the file to be opened.
  • duplicate_filehandle (bool) – By default, file handles passed either directly or through File-like objects will be duplicated before passing them to htslib. The duplication prevents issues where the same stream will be closed by htslib and through destruction of the high-level python object. Set to False to turn off duplication.
  • ignore_truncation (bool) – Issue a warning, instead of raising an error if the current file appears to be truncated due to a missing EOF marker. Only applies to bgzipped formats. (Default=False)
check_index(self)

return True if index is present.

Raises:
  • AttributeError – if htsfile is SAM formatted and thus has no index.
  • ValueError – if htsfile is closed or index could not be opened.
close(self)

closes the pysam.AlignmentFile.

count(self, reference=None, start=None, end=None, region=None, until_eof=False, read_callback='nofilter')

count the number of reads in region

The region is specified by reference, start and end. Alternatively, a samtools region string can be supplied.

A SAM file does not allow random access and if region or reference are given, an exception is raised.

Parameters:
  • reference (string) – reference_name of the genomic region (chromosome)
  • start (int) – start of the genomic region
  • end (int) – end of the genomic region
  • region (string) – a region string in samtools format.
  • until_eof (bool) – count until the end of the file, possibly including unmapped reads as well.
  • read_callback (string or function) –

    select a call-back to ignore reads when counting. It can be either a string with the following values:

    all
    skip reads in which any of the following flags are set: BAM_FUNMAP, BAM_FSECONDARY, BAM_FQCFAIL, BAM_FDUP
    nofilter
    uses every single read

    Alternatively, read_callback can be a function check_read(read) that should return True only for those reads that shall be included in the counting.
Raises:

ValueError – if the genomic coordinates are out of range or invalid.
count_coverage(self, reference=None, start=None, end=None, region=None, quality_threshold=15, read_callback='all')

count the coverage of genomic positions by reads in region.

The region is specified by reference, start and end. Alternatively, a samtools region string can be supplied. The coverage is computed per-base [ACGT].

Parameters:
  • reference (string) – reference_name of the genomic region (chromosome)
  • start (int) – start of the genomic region
  • end (int) – end of the genomic region
  • region (int) – a region string.
  • quality_threshold (int) – quality_threshold is the minimum quality score (in phred) a base has to reach to be counted.
  • read_callback (string or function) –

    select a call-back to ignore reads when counting. It can be either a string with the following values:

    all
    skip reads in which any of the following flags are set: BAM_FUNMAP, BAM_FSECONDARY, BAM_FQCFAIL, BAM_FDUP
    nofilter
    uses every single read

    Alternatively, read_callback can be a function check_read(read) that should return True only for those reads that shall be included in the counting.
Raises:

ValueError – if the genomic coordinates are out of range or invalid.
Returns:

four array.arrays of the same length in order A C G T
Return type:

tuple
fetch(self, reference=None, start=None, end=None, region=None, tid=None, until_eof=False, multiple_iterators=False)

fetch reads aligned in a region.

See AlignmentFile.parse_region() for more information on genomic regions.

Without a reference or region all mapped reads in the file will be fetched. The reads will be returned ordered by reference sequence, which will not necessarily be the order within the file. This mode of iteration still requires an index. If there is no index, use until_eof=True.

If only reference is set, all reads aligned to reference will be fetched.

A SAM file does not allow random access. If region or reference are given, an exception is raised.

FastaFile IteratorRow IteratorRow IteratorRow IteratorRow

Parameters:
  • until_eof (bool) – If until_eof is True, all reads from the current file position will be returned in order as they are within the file. Using this option will also fetch unmapped reads.
  • multiple_iterators (bool) – If multiple_iterators is True, multiple iterators on the same file can be used at the same time. The iterator returned will receive its own copy of a filehandle to the file effectively re-opening the file. Re-opening a file creates some overhead, so beware.
Returns:
Return type:

An iterator over a collection of reads.
Raises:

ValueError – if the genomic coordinates are out of range or invalid or the file does not permit random access to genomic coordinates.
find_introns(self, read_iterator)

Return a dictionary {(start, stop): count} Listing the intronic sites in the reads (identified by ‘N’ in the cigar strings), and their support ( = number of reads ).

read_iterator can be the result of a .fetch(...) call. Or it can be a generator filtering such reads. Example samfile.find_introns((read for read in samfile.fetch(...) if read.is_reverse)

get_reference_name(self, tid)

return reference name corresponding to numerical tid

get_tid(self, reference)

return the numerical tid corresponding to reference

returns -1 if reference is not known.

getrname(self, tid)

deprecated, use get_reference_name() instead

gettid(self, reference)

deprecated, use get_tid() instead

has_index(self)

return true if htsfile has an existing (and opened) index.

head(self, n, multiple_iterators=True)

return an iterator over the first n alignments.

This iterator is is useful for inspecting the bam-file.

Parameters:multiple_iterators (bool) – is set to True by default in order to avoid changing the current file position.
Returns:
Return type:an iterator over a collection of reads
header

two-level dictionay with header information from the file.

This is a read-only attribute.

The first level contains the record (HD, SQ, etc) and the second level contains the fields (VN, LN, etc).

The parser is validating and will raise an AssertionError if if encounters any record or field tags that are not part of the SAM specification. Use the pysam.AlignmentFile.text attribute to get the unparsed header.

The parsing follows the SAM format specification with the exception of the CL field. This option will consume the rest of a header line irrespective of any additional fields. This behaviour has been added to accommodate command line options that contain characters that are not valid field separators.

lengths

tuple of the lengths of the reference sequences. This is a read-only attribute. The lengths are in the same order as pysam.AlignmentFile.references

mapped

int with total number of mapped alignments according to the statistics recorded in the index. This is a read-only attribute.

mate(self, AlignedSegment read)

return the mate of AlignedSegment read.

Note

Calling this method will change the file position. This might interfere with any iterators that have not re-opened the file.

Note

This method is too slow for high-throughput processing. If a read needs to be processed with its mate, work from a read name sorted file or, better, cache reads.

Returns::class:`~pysam.AlignedSegment`
Return type:the mate
Raises:ValueError – if the read is unpaired or the mate is unmapped
next
nocoordinate

int with total number of reads without coordinates according to the statistics recorded in the index. This is a read-only attribute.

nreferences

“int with the number of reference sequences in the file. This is a read-only attribute.

parse_region(self, reference=None, start=None, end=None, region=None, tid=None)

parse alternative ways to specify a genomic region. A region can either be specified by reference, start and end. start and end denote 0-based, half-open intervals.

Alternatively, a samtools region string can be supplied.

If any of the coordinates are missing they will be replaced by the minimum (start) or maximum (end) coordinate.

Note that region strings are 1-based, while start and end denote an interval in python coordinates.

Returns:
  • tuple (a tuple of flag, tid, start and end. The)
  • flag indicates whether no coordinates were supplied and the
  • genomic region is the complete genomic space.
Raises:ValueError – for invalid or out of bounds regions.
pileup(self, reference=None, start=None, end=None, region=None, **kwargs)

perform a pileup within a region. The region is specified by reference, ‘start’ and ‘end’ (using 0-based indexing). Alternatively, a samtools ‘region’ string can be supplied.

Without ‘reference’ or ‘region’ all reads will be used for the pileup. The reads will be returned ordered by reference sequence, which will not necessarily be the order within the file.

Note that SAM formatted files do not allow random access. In these files, if a ‘region’ or ‘reference’ are given an exception is raised.

Note

‘all’ reads which overlap the region are returned. The first base returned will be the first base of the first read ‘not’ necessarily the first base of the region used in the query.

Parameters:stepper (string) –

The stepper controls how the iterator advances. Possible options for the stepper are

all
skip reads in which any of the following flags are set: BAM_FUNMAP, BAM_FSECONDARY, BAM_FQCFAIL, BAM_FDUP
nofilter
uses every single read
samtools
same filter and read processing as in csamtools pileup. This requires a ‘fastafile’ to be given.

fastafile : FastaFile object.

This is required for some of the steppers.
max_depth : int
Maximum read depth permitted. The default limit is ‘8000’.

truncate : bool

By default, the samtools pileup engine outputs all reads overlapping a region. If truncate is True and a region is given, only columns in the exact region specificied are returned.
Returns:
Return type:an iterator over genomic positions.
references

tuple with the names of reference sequences. This is a read-only attribute

text

string with the full contents of the sam file header as a string.

This is a read-only attribute.

See pysam.AlignmentFile.header to get a parsed representation of the header.

unmapped

int with total number of unmapped reads according to the statistics recorded in the index. This number of reads includes the number of reads without coordinates. This is a read-only attribute.

write(self, AlignedSegment read) → int

write a single pysam.AlignedSegment to disk.

Raises:ValueError – if the writing failed
Returns:int – this will be 0.
Return type:the number of bytes written. If the file is closed,

An AlignedSegment represents an aligned segment within a SAM/BAM file.

class pysam.AlignedSegment

Class representing an aligned segment.

This class stores a handle to the samtools C-structure representing an aligned read. Member read access is forwarded to the C-structure and converted into python objects. This implementation should be fast, as only the data needed is converted.

For write access, the C-structure is updated in-place. This is not the most efficient way to build BAM entries, as the variable length data is concatenated and thus needs to be resized if a field is updated. Furthermore, the BAM entry might be in an inconsistent state.

One issue to look out for is that the sequence should always be set before the quality scores. Setting the sequence will also erase any quality scores that were set previously.

aend

deprecated, reference_end instead

alen

deprecated, reference_length instead

aligned_pairs

deprecated, use get_aligned_pairs() instead

bin

properties bin

blocks

deprecated, use get_blocks() instead

cigar

deprecated, use cigartuples instead

cigarstring

the cigar alignment as a string.

The cigar string is a string of alternating integers and characters denoting the length and the type of an operation.

Note

The order length,operation is specified in the SAM format. It is different from the order of the cigar property.

Returns None if not present.

To unset the cigarstring, assign None or the empty string.

cigartuples

the cigar alignment. The alignment is returned as a list of tuples of (operation, length).

If the alignment is not present, None is returned.

The operations are:

M BAM_CMATCH 0
I BAM_CINS 1
D BAM_CDEL 2
N BAM_CREF_SKIP 3
S BAM_CSOFT_CLIP 4
H BAM_CHARD_CLIP 5
P BAM_CPAD 6
= BAM_CEQUAL 7
X BAM_CDIFF 8
B BAM_CBACK 9

Note

The output is a list of (operation, length) tuples, such as [(0, 30)]. This is different from the SAM specification and the cigarstring property, which uses a (length, operation) order, for example: 30M.

To unset the cigar property, assign an empty list or None.

compare(self, AlignedSegment other)

return -1,0,1, if contents in this are binary <,=,> to other

flag

properties flag

get_aligned_pairs(self, matches_only=False, with_seq=False)

a list of aligned read (query) and reference positions.

For inserts, deletions, skipping either query or reference position may be None.

Padding is currently not supported and leads to an exception.

Parameters:
  • matches_only (bool) – If True, only matched bases are returned - no None on either side.
  • with_seq (bool) – If True, return a third element in the tuple containing the reference sequence. Substitutions are lower-case. This option requires an MD tag to be present.
Returns:

aligned_pairs
Return type:

list of tuples
get_blocks(self)

a list of start and end positions of aligned gapless blocks.

The start and end positions are in genomic coordinates.

Blocks are not normalized, i.e. two blocks might be directly adjacent. This happens if the two blocks are separated by an insertion in the read.

get_cigar_stats(self)

summary of operations in cigar string.

The output order in the array is “MIDNSHP=X” followed by a field for the NM tag. If the NM tag is not present, this field will always be 0.

M BAM_CMATCH 0
I BAM_CINS 1
D BAM_CDEL 2
N BAM_CREF_SKIP 3
S BAM_CSOFT_CLIP 4
H BAM_CHARD_CLIP 5
P BAM_CPAD 6
= BAM_CEQUAL 7
X BAM_CDIFF 8
B BAM_CBACK 9
NM NM tag 10

If no cigar string is present, empty arrays will be returned.

Returns:arrays – each cigar operation, the second contains the number of blocks for each cigar operation.
Return type:two arrays. The first contains the nucleotide counts within
get_overlap(self, uint32_t start, uint32_t end)

return number of aligned bases of read overlapping the interval start and end on the reference sequence.

Return None if cigar alignment is not available.

get_reference_positions(self, full_length=False)

a list of reference positions that this read aligns to.

By default, this method only returns positions in the reference that are within the alignment. If full_length is set, None values will be included for any soft-clipped or unaligned positions within the read. The returned list will thus be of the same length as the read.

get_reference_sequence(self)

return the reference sequence.

This method requires the MD tag to be set.

get_tag(self, tag, with_value_type=False)

retrieves data from the optional alignment section given a two-letter tag denoting the field.

The returned value is cast into an appropriate python type.

This method is the fastest way to access the optional alignment section if only few tags need to be retrieved.

Parameters:
  • tag – data tag.
  • with_value_type (Optional[bool]) – if set to True, the return value is a tuple of (tag value, type code). (default False)
Returns:

  • A python object with the value of the tag. The type of the
  • object depends on the data type in the data record.
Raises:

KeyError – If tag is not present, a KeyError is raised.
get_tags(self, with_value_type=False)

the fields in the optional aligment section.

Returns a list of all fields in the optional alignment section. Values are converted to appropriate python values. For example:

[(NM, 2), (RG, “GJP00TM04”)]

If with_value_type is set, the value type as encode in the AlignedSegment record will be returned as well:

[(NM, 2, “i”), (RG, “GJP00TM04”, “Z”)]

This method will convert all values in the optional alignment section. When getting only one or few tags, please see get_tag() for a quicker way to achieve this.

has_tag(self, tag)

returns true if the optional alignment section contains a given tag.

infer_query_length(self, always=False)

infer query length from sequence or CIGAR alignment.

This method deduces the query length from the CIGAR alignment but does not include hard-clipped bases.

Returns None if CIGAR alignment is not present.

If always is set to True, infer_read_length is used instead. This is deprecated and only present for backward compatibility.

infer_read_length(self)

infer read length from CIGAR alignment.

This method deduces the read length from the CIGAR alignment including hard-clipped bases.

Returns None if CIGAR alignment is not present.

inferred_length

deprecated, use infer_query_length() instead

is_duplicate

true if optical or PCR duplicate

is_paired

true if read is paired in sequencing

is_proper_pair

true if read is mapped in a proper pair

is_qcfail

true if QC failure

is_read1

true if this is read1

is_read2

true if this is read2

is_reverse

true if read is mapped to reverse strand

is_secondary

true if not primary alignment

is_supplementary

true if this is a supplementary alignment

is_unmapped

true if read itself is unmapped

isize

deprecated, use template_length instead

mapping_quality

mapping quality

mapq

deprecated, use mapping_quality instead

mate_is_reverse

true is read is mapped to reverse strand

mate_is_unmapped

true if the mate is unmapped

mpos

deprecated, use next_reference_start instead

mrnm

deprecated, use next_reference_id instead

next_reference_id

the reference id of the mate/next read.

next_reference_name

reference name of the mate/next read (None if no AlignmentFile is associated)

next_reference_start

the position of the mate/next read.

opt(self, tag)

deprecated, use get_tag() instead

overlap(self)

deprecated, use get_overlap() instead

pnext

deprecated, use next_reference_start instead

pos

deprecated, use reference_start instead

positions

deprecated, use get_reference_positions() instead

qend

deprecated, use query_alignment_end instead

qlen

deprecated, use query_alignment_length instead

qname

deprecated, use query_name instead

qqual

deprecated, query_alignment_qualities instead

qstart

deprecated, use query_alignment_start instead

qual

deprecated, query_qualities instead

query

deprecated, query_alignment_sequence instead

query_alignment_end

end index of the aligned query portion of the sequence (0-based, exclusive)

This the index just past the last base in seq that is not soft-clipped.

query_alignment_length

length of the aligned query sequence.

This is equal to qend - qstart

query_alignment_qualities

aligned query sequence quality values (None if not present). These are the quality values that correspond to query, that is, they exclude qualities of soft clipped bases. This is equal to qual[qstart:qend].

Quality scores are returned as a python array of unsigned chars. Note that this is not the ASCII-encoded value typically seen in FASTQ or SAM formatted files. Thus, no offset of 33 needs to be subtracted.

This property is read-only.

query_alignment_sequence

aligned portion of the read.

This is a substring of seq that excludes flanking bases that were soft clipped (None if not present). It is equal to seq[qstart:qend].

SAM/BAM files may include extra flanking bases that are not part of the alignment. These bases may be the result of the Smith-Waterman or other algorithms, which may not require alignments that begin at the first residue or end at the last. In addition, extra sequencing adapters, multiplex identifiers, and low-quality bases that were not considered for alignment may have been retained.

query_alignment_start

start index of the aligned query portion of the sequence (0-based, inclusive).

This the index of the first base in seq that is not soft-clipped.

query_length

the length of the query/read.

This value corresponds to the length of the sequence supplied in the BAM/SAM file. The length of a query is 0 if there is no sequence in the BAM/SAM file. In those cases, the read length can be inferred from the CIGAR alignment, see pysam.AlignedSegment.infer_query_length().

The length includes soft-clipped bases and is equal to len(query_sequence).

This property is read-only but can be set by providing a sequence.

Returns 0 if not available.

query_name

the query template name (None if not present)

query_qualities

**read sequence base qualities, including* – term* – soft clipped bases (None if not present).

Quality scores are returned as a python array of unsigned chars. Note that this is not the ASCII-encoded value typically seen in FASTQ or SAM formatted files. Thus, no offset of 33 needs to be subtracted.

Note that to set quality scores the sequence has to be set beforehand as this will determine the expected length of the quality score array.

This method raises a ValueError if the length of the quality scores and the sequence are not the same.

query_sequence

read sequence bases, including soft clipped bases (None if not present).

Note that assigning to seq will invalidate any quality scores. Thus, to in-place edit the sequence and quality scores, copies of the quality scores need to be taken. Consider trimming for example:

q = read.query_qualities
read.query_squence = read.query_sequence[5:10]
read.query_qualities = q[5:10]

The sequence is returned as it is stored in the BAM file. Some mappers might have stored a reverse complement of the original read sequence.

reference_end

aligned reference position of the read on the reference genome.

reference_end points to one past the last aligned residue. Returns None if not available (read is unmapped or no cigar alignment present).

reference_id

reference ID

Note

This field contains the index of the reference sequence in the sequence dictionary. To obtain the name of the reference sequence, use pysam.AlignmentFile.getrname()

reference_length

aligned length of the read on the reference genome.

This is equal to aend - pos. Returns None if not available.

reference_name

reference name (None if no AlignmentFile is associated)

reference_start

0-based leftmost coordinate

rlen

deprecated, query_length instead

rname

deprecated, use reference_id instead

rnext

deprecated, use next_reference_id instead

seq

deprecated, use query_sequence instead

setTag(self, tag, value, value_type=None, replace=True)

deprecated, use set_tag() instead

set_tag(self, tag, value, value_type=None, replace=True)

sets a particular field tag to value in the optional alignment section.

value_type describes the type of value that is to entered into the alignment record.. It can be set explicitly to one of the valid one-letter type codes. If unset, an appropriate type will be chosen automatically.

An existing value of the same tag will be overwritten unless replace is set to False. This is usually not recommened as a tag may only appear once in the optional alignment section.

If value is None, the tag will be deleted.

set_tags(self, tags)

sets the fields in the optional alignmest section with a list of (tag, value) tuples.

The value type of the values is determined from the python type. Optionally, a type may be given explicitly as a third value in the tuple, For example:

x.set_tags([(NM, 2, “i”), (RG, “GJP00TM04”, “Z”)]

This method will not enforce the rule that the same tag may appear only once in the optional alignment section.

tags

deprecated, use get_tags() instead

template_length

the observed query template length

tid

deprecated, use reference_id instead

tlen

deprecated, use template_length instead

tostring(self, AlignmentFile_t htsfile)

returns a string representation of the aligned segment.

The output format is valid SAM format.

Parameters:-- AlignmentFile object to map numerical (htsfile) – identifiers to chromosome names.
class pysam.PileupColumn

A pileup of reads at a particular reference sequence position (column). A pileup column contains all the reads that map to a certain target base.

This class is a proxy for results returned by the samtools pileup engine. If the underlying engine iterator advances, the results of this column will change.

nsegments

number of reads mapping to this column.

pileups

list of reads (pysam.PileupRead) aligned to this column

reference_id

the reference sequence number as defined in the header

reference_name

reference name (None if no AlignmentFile is associated)

reference_pos

the position in the reference sequence (0-based).

class pysam.PileupRead

Representation of a read aligned to a particular position in the reference sequence.

alignment

a pysam.AlignedSegment object of the aligned read

indel

indel length for the position following the current pileup site.

This quantity peeks ahead to the next cigar operation in this alignment. If the next operation is an insertion, indel will be positive. If the next operation is a deletion, it will be negation. 0 if the next operation is not an indel.

is_del

1 iff the base on the padded read is a deletion

is_head

1 iff the base on the padded read is the left-most base.

is_refskip

1 iff the base on the padded read is part of CIGAR N op.

is_tail

1 iff the base on the padded read is the right-most base.

level

the level of the read in the “viewer” mode. Note that this value is currently not computed.

query_position

position of the read base at the pileup site, 0-based. None if is_del or is_refskip is set.

query_position_or_next

position of the read base at the pileup site, 0-based.

If the current position is a deletion, returns the next aligned base.

class pysam.IndexedReads(AlignmentFile samfile, int multiple_iterators=True)

*(AlignmentFile samfile, multiple_iterators=True)

Index a Sam/BAM-file by query name while keeping the original sort order intact.

The index is kept in memory and can be substantial.

By default, the file is re-openend to avoid conflicts if multiple operators work on the same file. Set multiple_iterators = False to not re-open samfile.

Parameters:
  • samfile (AlignmentFile) – File to be indexed.
  • multiple_iterators (bool) – Flag indicating whether the file should be reopened. Reopening prevents existing iterators being affected by the indexing.
build(self)

build the index.

find(self, query_name)

find query_name in index.

Returns:Returns an iterator over all reads with query_name.
Return type:IteratorRowSelection
Raises:KeyError – if the query_name is not in the index.
Tabix files

TabixFile opens tabular files that have been indexed with tabix.

class pysam.TabixFile

Random access to bgzf formatted files that have been indexed by tabix.

The file is automatically opened. The index file of file <filename> is expected to be called <filename>.tbi by default (see parameter index).

Parameters:
  • filename (string) – Filename of bgzf file to be opened.
  • index (string) – The filename of the index. If not set, the default is to assume that the index is called ``filename.tbi`
  • mode (char) – The file opening mode. Currently, only r is permitted.
  • parser (pysam.Parser) – sets the default parser for this tabix file. If parser is None, the results are returned as an unparsed string. Otherwise, parser is assumed to be a functor that will return parsed data (see for example asTuple and asGTF).
  • encoding (string) – The encoding passed to the parser
Raises:
close(self)

closes the pysam.TabixFile.

contigs

list of chromosome names

fetch(self, reference=None, start=None, end=None, region=None, parser=None, multiple_iterators=False)

fetch one or more rows in a region using 0-based indexing. The region is specified by reference, start and end. Alternatively, a samtools region string can be supplied.

Without reference or region all entries will be fetched.

If only reference is set, all reads matching on reference will be fetched.

If parser is None, the default parser will be used for parsing.

Set multiple_iterators to true if you will be using multiple iterators on the same file at the same time. The iterator returned will receive its own copy of a filehandle to the file effectively re-opening the file. Re-opening a file creates some overhead, so beware.

header

the file header.

The file header consists of the lines at the beginning of a file that are prefixed by the comment character #.

Note

The header is returned as an iterator presenting lines without the newline character.

Note

The header is only available for local files. For remote files an Attribute Error is raised.

To iterate over tabix files, use tabix_iterator():

pysam.tabix_iterator(infile, parser)

return an iterator over all entries in a file.

Results are returned parsed as specified by the parser. If parser is None, the results are returned as an unparsed string. Otherwise, parser is assumed to be a functor that will return parsed data (see for example asTuple and asGTF).

pysam.tabix_compress(filename_in, filename_out, force=False)

compress filename_in writing the output to filename_out.

Raise an IOError if filename_out already exists, unless force is set.

pysam.tabix_index(filename, force=False, seq_col=None, start_col=None, end_col=None, preset=None, meta_char='#', zerobased=False, int min_shift=-1)

index tab-separated filename using tabix.

An existing index will not be overwritten unless force is set.

The index will be built from coordinates in columns seq_col, start_col and end_col.

The contents of filename have to be sorted by contig and position - the method does not check if the file is sorted.

Column indices are 0-based. Coordinates in the file are assumed to be 1-based.

If preset is provided, the column coordinates are taken from a preset. Valid values for preset are “gff”, “bed”, “sam”, “vcf”, psltbl”, “pileup”.

Lines beginning with meta_char and the first line_skip lines will be skipped.

If filename does not end in ”.gz”, it will be automatically compressed. The original file will be removed and only the compressed file will be retained.

If filename ends in gz, the file is assumed to be already compressed with bgzf.

min-shift sets the minimal interval size to 1<<INT; 0 for the old tabix index. The default of -1 is changed inside htslib to the old tabix default of 0.

returns the filename of the compressed data

class pysam.asTuple

converts a tabix row into a python tuple.

A field in a row is accessed by numeric index.

class pysam.asVCF

converts a tabix row into a VCF record with the following fields:

Column Field Contents
1 contig chromosome
2 pos chromosomal position, zero-based
3 id id
4 ref reference allele
5 alt alternate alleles
6 qual quality
7 filter filter
8 info info
9 format format specifier.

Access to genotypes is via index:

contig = vcf.contig
first_sample_genotype = vcf[0]
second_sample_genotype = vcf[1]
class pysam.asBed

converts a tabix row into a bed record with the following fields:

Column Field Contents
1 contig contig
2 start genomic start coordinate (zero-based)
3 end genomic end coordinate plus one (zero-based)
4 name name of feature.
5 score score of feature
6 strand strand of feature
7 thickStart thickStart
8 thickEnd thickEnd
9 itemRGB itemRGB
10 blockCount number of bocks
11 blockSizes ‘,’ separated string of block sizes
12 blockStarts ‘,’ separated string of block genomic start positions

Only the first three fields are required. Additional fields are optional, but if one is defined, all the preceding need to be defined as well.

class pysam.asGTF

converts a tabix row into a GTF record with the following fields:

Column Name Content
1 contig the chromosome name
2 feature The feature type
3 source The feature source
4 start genomic start coordinate (0-based)
5 end genomic end coordinate (0-based)
6 score feature score
7 strand strand
8 frame frame
9 attributes the attribute field

GTF formatted entries also define the following fields that are derived from the attributes field:

Name Content
gene_id the gene identifier
transcript_id the transcript identifier
Fasta files
class pysam.FastaFile

Random access to fasta formatted files that have been indexed by faidx.

The file is automatically opened. The index file of file <filename> is expected to be called <filename>.fai.

Parameters:
  • filename (string) – Filename of fasta file to be opened.
  • filepath_index (string) – Optional, filename of the index. By default this is the filename + ”.fai”.
Raises:
close(self)

close the file.

closed

“bool indicating the current state of the file object. This is a read-only attribute; the close() method changes the value.

fetch(self, reference=None, start=None, end=None, region=None)

fetch sequences in a region.

A region can either be specified by reference, start and end. start and end denote 0-based, half-open intervals.

Alternatively, a samtools region string can be supplied.

If any of the coordinates are missing they will be replaced by the minimum (start) or maximum (end) coordinate.

Note that region strings are 1-based, while start and end denote an interval in python coordinates. The region is specified by reference, start and end.

Returns:

string
Return type:

a string with the sequence specified by the region.
Raises:
filename

filename associated with this object. This is a read-only attribute.

get_reference_length(self, reference)

return the length of reference.

is_open(self)

return true if samfile has been opened.

lengths

tuple with the lengths of reference sequences.

nreferences

“int with the number of reference sequences in the file. This is a read-only attribute.

references

tuple with the names of reference sequences.

Fastq files
class pysam.FastxFile

Stream access to fasta or fastq formatted files.

The file is automatically opened.

Entries in the file can be both fastq or fasta formatted or even a mixture of the two.

This file object permits iterating over all entries in the file. Random access is not implemented. The iteration returns objects of type FastqProxy

Parameters:
  • filename (string) – Filename of fasta/fastq file to be opened.
  • persist (bool) – If True (default) make a copy of the entry in the file during iteration. If set to False, no copy will be made. This will permit faster iteration, but an entry will not persist when the iteration continues.

Notes

Prior to version 0.8.2, this was called FastqFile.

Raises:IOError – if file could not be opened

Examples

>>> with pysam.FastxFile(filename) as fh:
...    for entry in fh:
...        print(entry.name)
...        print(entry.sequence)
...        print(entry.comment)
...        print(entry.quality)
>>> with pysam.FastxFile(filename) as fin, open(out_filename, mode='w') as fout:
...    for entry in fin:
...        fout.write(str(entry))
close(self)

close the file.

closed

“bool indicating the current state of the file object. This is a read-only attribute; the close() method changes the value.

filename

string with the filename associated with this object.

is_open(self)

return true if samfile has been opened.

next
class pysam.FastqProxy

A single entry in a fastq file.

get_quality_array(self, int offset=33) → array

return quality values as integer array after subtracting offset.

name

The name of each entry in the fastq file.

quality

The quality score of each entry in the fastq file, represented as a string.

sequence

The sequence of each entry in the fastq file.

VCF files
class pysam.VariantFile(*args, **kwargs)

(filename, mode=None, index_filename=None, header=None, drop_samples=False, duplicate_filehandle=True, ignore_truncation=False)

A VCF/BCF formatted file. The file is automatically opened.

If an index for a variant file exists (.csi or .tbi), it will be opened automatically. Without an index random access to records via fetch() is disabled.

For writing, a VariantHeader object must be provided, typically obtained from another VCF file/BCF file.

Parameters:
  • mode (string) –

    mode should be r for reading or w for writing. The default is text mode (VCF). For binary (BCF) I/O you should append b for compressed or u for uncompressed BCF output.

    If b is present, it must immediately follow r or w. Valid modes are r, w, wh, rb, wb, wbu and wb0. For instance, to open a BCF formatted file for reading, type:

    f = pysam.VariantFile('ex1.bcf','r')

    If mode is not specified, we will try to auto-detect the file type. All of the following should work:

    f1 = pysam.VariantFile('ex1.bcf')
f2 = pysam.VariantFile('ex1.vcf')
f3 = pysam.VariantFile('ex1.vcf.gz')
  • index_filename (string) – Explicit path to an index file.
  • header (VariantHeader) – VariantHeader object required for writing.
  • drop_samples (bool) – Ignore sample information when reading.
  • duplicate_filehandle (bool) – By default, file handles passed either directly or through File-like objects will be duplicated before passing them to htslib. The duplication prevents issues where the same stream will be closed by htslib and through destruction of the high-level python object. Set to False to turn off duplication.
  • ignore_truncation (bool) – Issue a warning, instead of raising an error if the current file appears to be truncated due to a missing EOF marker. Only applies to bgzipped formats. (Default=False)
close(self)

closes the pysam.VariantFile.

copy(self)
fetch(self, contig=None, start=None, stop=None, region=None, reopen=False)

fetch records in a region using 0-based indexing. The region is specified by contig, start and end. Alternatively, a samtools region string can be supplied.

Without contig or region all mapped records will be fetched. The records will be returned ordered by contig, which will not necessarily be the order within the file.

Set reopen to true if you will be using multiple iterators on the same file at the same time. The iterator returned will receive its own copy of a filehandle to the file effectively re-opening the file. Re-opening a file incurrs some overhead, so use with care.

If only contig is set, all records on contig will be fetched. If both region and contig are given, an exception is raised.

Note that a bgzipped VCF.gz file without a tabix/CSI index (.tbi/.csi) or a BCF file without a CSI index can only be read sequentially.

new_record(self, *args, **kwargs)

Create a new empty VariantRecord.

See VariantHeader.new_record()

next
open(self, filename, mode='r', index_filename=None, VariantHeader header=None, drop_samples=False, duplicate_filehandle=True, ignore_truncation=False)

open a vcf/bcf file.

If open is called on an existing VariantFile, the current file will be closed and a new file will be opened.

reset(self)

reset file position to beginning of file just after the header.

subset_samples(self, include_samples)

Read only a subset of samples to reduce processing time and memory. Must be called prior to retrieving records.

write(self, VariantRecord record) → int

write a single pysam.VariantRecord to disk.

returns the number of bytes written.

class pysam.VariantHeader

header information for a VariantFile object

add_line(self, line)

Add a metadata line to this header

add_meta(self, key, value=None, items=None)

Add metadata to this header

add_record(self, VariantHeaderRecord record)

Add an existing VariantHeaderRecord to this header

add_sample(self, name)

Add a new sample to this header

alts

alt metadata (dict ID->record).

The data returned just a snapshot of alt records, is created every time the property is requested, and modifications will not be reflected in the header metadata and vice versa.

i.e. it is just a dict that reflects the state of alt records at the time it is created.

contigs

contig information (VariantHeaderContigs)

copy(self)
filters

filter metadata (VariantHeaderMetadata)

formats

format metadata (VariantHeaderMetadata)

info

info metadata (VariantHeaderMetadata)

merge(self, VariantHeader header)
new_record(self, contig=None, start=0, stop=0, alleles=None, id=None, qual=None, filter=None, info=None, samples=None, **kwargs)

Create a new empty VariantRecord.

Arguments are currently experimental. Use with caution and expect changes in upcoming releases.

records

header records (VariantHeaderRecords)

samples
version

VCF version

class pysam.VariantRecord(*args, **kwargs)

Variant record

alleles

tuple of reference allele followed by alt alleles

alts

tuple of alt alleles

chrom

chromosome/contig name

contig

chromosome/contig name

copy(self)

return a copy of this VariantRecord object

filter

filter information (see VariantRecordFilter)

format

sample format metadata (see VariantRecordFormat)

id

record identifier or None if not available

info

info data (see VariantRecordInfo)

pos

record start position on chrom/contig (1-based inclusive)

qual

phred scaled quality score or None if not available

ref

reference allele

rid

internal reference id number

rlen

record length on chrom/contig (aka rec.stop - rec.start)

samples

sample data (see VariantRecordSamples)

start

record start position on chrom/contig (0-based inclusive)

stop

record stop position on chrom/contig (0-based exclusive)

translate(self, VariantHeader dst_header)
class pysam.VariantHeaderRecord(*args, **kwargs)

header record from a VariantHeader object

attrs

sequence of additional header attributes

get(self, key, default=None)

D.get(k[,d]) -> D[k] if k in D, else d. d defaults to None.

items(self)

D.items() -> list of D’s (key, value) pairs, as 2-tuples

iteritems(self)

D.iteritems() -> an iterator over the (key, value) items of D

iterkeys(self)

D.iterkeys() -> an iterator over the keys of D

itervalues(self)

D.itervalues() -> an iterator over the values of D

key

header key (the part before ‘=’, in FILTER/INFO/FORMAT/contig/fileformat etc.)

keys(self)

D.keys() -> list of D’s keys

pop(self, key, default=_nothing)
remove(self)
type

header type – FILTER, INFO, FORMAT, CONTIG, STRUCTURED, or GENERIC

update(self, items=None, **kwargs)

D.update([E, ]**F) -> None.

Update D from dict/iterable E and F.

value

header value. Set only for generic lines, None for FILTER/INFO, etc.

values(self)

D.values() -> list of D’s values

Working with BAM/CRAM/SAM-formatted files

Opening a file

To begin with, import the pysam module and open a pysam.AlignmentFile:

import pysam
samfile = pysam.AlignmentFile("ex1.bam", "rb")

The above command opens the file ex1.bam for reading. The b qualifier indicates that this is a BAM file. To open a SAM file, type:

import pysam
samfile = pysam.AlignmentFile("ex1.sam", "r")

CRAM files are identified by a c qualifier:

import pysam
samfile = pysam.AlignmentFile("ex1.cram", "rc")

Fetching reads mapped to a region

Reads are obtained through a call to the pysam.AlignmentFile.fetch() method which returns an iterator. Each call to the iterator will returns a pysam.AlignedSegment object:

iter = samfile.fetch("seq1", 10, 20)
for x in iter:
    print (str(x))

pysam.AlignmentFile.fetch() returns all reads overlapping a region sorted by the first aligned base in the reference sequence. Note that it will also return reads that are only partially overlapping with the region. Thus the reads returned might span a region that is larger than the one queried.

Using the pileup-engine

In contrast to fetching, the pileup engine returns for each base in the reference sequence the reads that map to that particular position. In the typical view of reads stacking vertically on top of the reference sequence similar to a multiple alignment, fetching iterates over the rows of this implied multiple alignment while a pileup iterates over the columns.

Calling pileup() will return an iterator over each column (reference base) of a specified region. Each call to the iterator returns an object of the type pysam.PileupColumn that provides access to all the reads aligned to that particular reference position as well as some additional information:

iter = samfile.pileup('seq1', 10, 20)
for x in iter:
   print (str(x))

Creating BAM/CRAM/SAM files from scratch

The following example shows how a new BAM file is constructed from scratch. The important part here is that the pysam.AlignmentFile class needs to receive the sequence identifiers. These can be given either as a dictionary in a header structure, as lists of names and sizes, or from a template file. Here, we use a header dictionary:

header = { 'HD': {'VN': '1.0'},
            'SQ': [{'LN': 1575, 'SN': 'chr1'},
                   {'LN': 1584, 'SN': 'chr2'}] }

with pysam.AlignmentFile(tmpfilename, "wb", header=header) as outf:
    a = pysam.AlignedSegment()
    a.query_name = "read_28833_29006_6945"
    a.query_sequence="AGCTTAGCTAGCTACCTATATCTTGGTCTTGGCCG"
    a.flag = 99
    a.reference_id = 0
    a.reference_start = 32
    a.mapping_quality = 20
    a.cigar = ((0,10), (2,1), (0,25))
    a.next_reference_id = 0
    a.next_reference_start=199
    a.template_length=167
    a.query_qualities = pysam.qualitystring_to_array("<<<<<<<<<<<<<<<<<<<<<:<9/,&,22;;<<<")
    a.tags = (("NM", 1),
              ("RG", "L1"))
    outf.write(a)

Using streams

Pysam does not support reading and writing from true python file objects, but it does support reading and writing from stdin and stdout. The following example reads from stdin and writes to stdout:

infile = pysam.AlignmentFile("-", "r")
outfile = pysam.AlignmentFile("-", "w", template=infile)
for s in infile:
    outfile.write(s)

It will also work with BAM files. The following script converts a BAM formatted file on stdin to a SAM formatted file on stdout:

infile = pysam.AlignmentFile("-", "rb")
outfile = pysam.AlignmentFile("-", "w", template=infile)
for s in infile:
    outfile.write(s)

Note that the file open mode needs to changed from r to rb.

Using samtools commands within python

Commands available in csamtools are available as simple function calls. Command line options are provided as arguments. For example:

pysam.sort("-o", "output.bam", "ex1.bam")

corresponds to the command line:

samtools sort -o output.bam ex1.bam

Or for example:

pysam.sort("-m", "1000000", "-o", "output.bam", "ex1.bam")

In order to get usage information, try:

print(pysam.sort.usage())

Argument errors raise a pysam.SamtoolsError:

pysam.sort()

Traceback (most recent call last):
File "x.py", line 12, in <module>
  pysam.sort()
File "/build/lib.linux-x86_64-2.6/pysam/__init__.py", line 37, in __call__
  if retval: raise SamtoolsError( "\n".join( stderr ) )
pysam.SamtoolsError: 'Usage: samtools sort [-n] [-m <maxMem>] <in.bam> <out.prefix>\n'

Messages from csamtools on stderr are captured and are available using the getMessages() method:

pysam.sort.getMessage()

Note that only the output from the last invocation of a command is stored.

In order for pysam to make the output of samtools commands accessible the stdout stream needs to be redirected. This is the default behaviour, but can cause problems in environments such as the ipython notebook. A solution is to pass the catch_stdout keyword argument:

pysam.sort(catch_stdout=False)

Note that this means that output from commands which produce output on stdout will not be available. The only solution is to run samtools commands through subprocess.

Working with tabix-indexed files

To open a tabular file that has been indexed with tabix, use TabixFile:

import pysam
tbx = pysam.TabixFile("example.bed.gz")

Similar to fetch, intervals within a region can be retrieved by calling fetch():

for row in tbx.fetch("chr1", 1000, 2000):
     print (str(row))

This will return a tuple-like data structure in which columns can be retrieved by numeric index:

for row in tbx.fetch(“chr1”, 1000, 2000):
print (“chromosome is”, row[0])

By providing a parser to fetch or TabixFile, the data will we presented in parsed form:

for row in tbx.fetch("chr1", 1000, 2000, parser=pysam.asTuple()):
     print ("chromosome is", row.contig)
     print ("first field (chrom)=", row[0])

Pre-built parsers are available for bed (asBed) formatted files and gtf (asGTF) formatted files. Thus, additional fields become available through named access, for example:

for row in tbx.fetch("chr1", 1000, 2000, parser=pysam.asBed()):
     print ("name is", row.name)

Working with VCF/BCF formatted files

To iterate through a VCF/BCF formatted file use VariantFile:

from pysam import VariantFile

bcf_in = VariantFile("test.bcf")  # auto-detect input format
bcf_out = VariantFile('-', 'w', header=bcf_in.header)

for rec in bcf_in.fetch('chr1', 100000, 200000):
    bcf_out.write(rec)

_pysam.VariantFile.fetch() iterates over VariantRecord objects which provides access to simple variant attributes such as contig, pos, ref:

for rec in bcf_in.fetch():
    print (rec.pos)

but also to complex attributes such as the contents to the info, format and genotype columns. These complex attributes are views on the underlying htslib data structures and provide dictionary-like access to the data:

for rec in bcf_in.fetch():
    print (rec.info)
    print (rec.info.keys())
    print (rec.info["DP"])

The header attribute (VariantHeader) provides access information stored in the vcf header. The complete header can be printed:

>>> print (bcf_in.header)
##fileformat=VCFv4.2
##FILTER=<ID=PASS,Description="All filters passed">
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=1000GenomesPilot-NCBI36
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples
With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=.,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build
129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
##contig=<ID=M>
##contig=<ID=17>
##contig=<ID=20>
##bcftools_viewVersion=1.3+htslib-1.3
##bcftools_viewCommand=view -O b -o example_vcf42.bcf
example_vcf42.vcf.gz
#CHROM  POS     ID      REF     ALT     QUAL    FILTER  INFO   FORMAT    NA00001 NA00002 NA0000

Individual contents such as contigs, info fields, samples, formats can be retrieved as attributes from header:

>>> print (bcf_in.header.contigs)
<pysam.cbcf.VariantHeaderContigs object at 0xf250f8>

To convert these views to native python types, iterate through the views:

>>> print list((bcf_in.header.contigs))
['M', '17', '20']
>>> print list((bcf_in.header.filters))
['PASS', 'q10', 's50']
>>> print list((bcf_in.header.info))
['NS', 'DP', 'AF', 'AA', 'DB', 'H2']
>>> print list((bcf_in.header.samples))
['NA00001', 'NA00002', 'NA00003']

Alternatively, it is possible to iterate through all records in the header returning objects of type VariantHeaderRecord::

>>> for x in bcf_in.header.records:
>>>    print (x)
>>>    print (x.type, x.key)
GENERIC fileformat
FILTER FILTER
GENERIC fileDate
GENERIC source
GENERIC reference
GENERIC phasing
INFO INFO
INFO INFO
INFO INFO
INFO INFO
INFO INFO
INFO INFO
FILTER FILTER
FILTER FILTER
FORMAT FORMAT
FORMAT FORMAT
FORMAT FORMAT
FORMAT FORMAT
CONTIG contig
CONTIG contig
CONTIG contig
GENERIC bcftools_viewVersion
GENERIC bcftools_viewCommand

Extending pysam

Using pyximport, it is (relatively) straight-forward to access pysam internals and the underlying samtools library. An example is provided in the tests directory. The example emulates the samtools flagstat command and consists of three files:

  1. The main script pysam_flagstat.py. The important lines in this script are:

    import pyximport
pyximport.install()
import _pysam_flagstat

...

flag_counts = _pysam_flagstat.count(pysam_in)

    The first part imports, sets up pyximport and imports the cython module _pysam_flagstat. The second part calls the count method in _pysam_flagstat.

  2. The cython implementation _pysam_flagstat.pyx. This script imports the pysam API via:

    from pysam.calignmentfile cimport AlignmentFile, AlignedSegment

    This statement imports, amongst others, AlignedSegment into the namespace. Speed can be gained from declaring variables. For example, to efficiently iterate over a file, an AlignedSegment object is declared:

    # loop over samfile
cdef AlignedSegment read
for read in samfile:
    ...

  3. A pyxbld providing pyximport with build information. Required are the locations of the samtools and pysam header libraries of a source installation of pysam plus the csamtools.so shared library. For example:

    def make_ext(modname, pyxfilename):
    from distutils.extension import Extension
    import pysam
    return Extension(name=modname,
          sources=[pyxfilename],
          extra_link_args=pysam.get_libraries(),
          include_dirs=pysam.get_include(),
          define_macros=pysam.get_defines())

If the script pysam_flagstat.py is called the first time, pyximport will compile the cython extension _pysam_flagstat.pyx and make it available to the script. Compilation requires a working compiler and cython installation. Each time _pysam_flagstat.pyx is modified, a new compilation will take place.

pyximport comes with cython.

Installing pysam

Pysam provides a python interface to the functionality contained within the htslib C library. There are two ways that these two can be combined, builtin and external.

Builtin

The typical installation will be through pypi_:

pip install pysam

This will compile the builtin htslib source code within pysam.

htslib can be configured at compilation to turn on additional features such support using encrypted configurations, enable plugins, and more. See the htslib project for more information on these.

Pysam will attempt to configure htslib to turn on some advanced features. If these fail, for example due to missing library dependencies (libcurl, libcrypto), it will fall back to conservative defaults.

Options can be passed to the configure script explicitely by setting the environment variable HTSLIB_CONFIGURE_OPTIONS. For example:

export HTSLIB_CONFIGURE_OPTIONS=--enable-plugins
pip install pysam

External

pysam can be combined with an externally installed htslib library. This is a good way to avoid duplication of libraries. To link against an externally installed library, set the environment variables HTSLIB_LIBRARY_DIR and HTSLIB_INCLUDE_DIR before installing:

export HTSLIB_LIBRARY_DIR=/usr/local/lib
export HTSLIB_INCLUDE_DIR=/usr/local/include
pip install pysam

Note that the location of the file libhts.so needs to be known to the linker once you run pysam, for example by setting the environment-varirable LD_LIBRARY_PATH.

cython

pysam depends on cython to provide the connectivity to the htslib C library. The installation of the source tarball (.tar.gz) python 2.7 contains pre-built C-files and cython needs not be present during installation. However, when installing the source tarball on python 3 or building from the repository, these pre-built C-files are not present and cython needs to be installed beforehand.

FAQ

How should I cite pysam

Pysam has not been published in print. When refering pysam, please use the github URL: https://github.com/pysam-developers/pysam. As pysam is a wrapper around htslib and the samtools package, I suggest cite Li et al (2009) <http://www.ncbi.nlm.nih.gov/pubmed/19505943>.

Is pysam thread-safe?

Pysam is a mix of python and C code. Instructions within python are generally made thread-safe through python’s global interpreter lock (GIL_). This ensures that python data structures will always be in a consistent state.

If an external function outside python is called, the programmer has a choice to keep the GIL in place or to release it. Keeping the GIL in place will make sure that all python threads wait until the external function has completed. This is a safe option and ensures thread-safety.

Alternatively, the GIL can be released while the external function is called. This will allow other threads to run concurrently. This can be beneficial if the external function is expected to halt, for example when waiting for data to read or write. However, to achieve thread-safety, the external function needs to implememented with thread-safety in mind. This means that there can be no shared state between threads, or if there is shared, it needs to be controlled to prevent any access conflicts.

Pysam generally uses the latter option and aims to release the GIL for I/O intensive tasks. This is generally fine, but thread-safety of all parts have not been fully tested.

A related issue is when different threads read from the same file objec - or the same thread uses two iterators over a file. There is only a single file-position for each opened file. To prevent this from hapeding, use the option mulitple_iterator=True when calling a fetch() method. This will return an iterator on a newly opened file.

pysam coordinates are wrong

pysam uses 0-based coordinates and the half-open notation for ranges as does python. Coordinates and intervals reported from pysam always follow that convention.

Confusion might arise as different file formats might have different conventions. For example, the SAM format is 1-based while the BAM format is 0-based. It is important to remember that pysam will always conform to the python convention and translate to/from the file format automatically.

The only exception is the region string in the fetch() and pileup() methods. This string follows the convention of the samtools command line utilities. The same is true for any coordinates passed to the samtools command utilities directly, such as pysam.mpileup().

Calling pysam.fetch() confuses existing iterators

The following code will cause unexpected behaviour:

samfile = pysam.AlignmentFile("pysam_ex1.bam", "rb")

iter1 = samfile.fetch("chr1")
print (iter1.next().reference_id)
iter2 = samfile.fetch("chr2")
print (iter2.next().reference_id)
print (iter1.next().reference_id)

This will give the following output:

0
1
Traceback (most recent call last):
  File "xx.py", line 8, in <module>
    print iter1.next().reference_id
  File "calignmentfile.pyx", line 1408, in
  pysam.calignmentfile.IteratorRowRegion.__next__
  (pysam/calignmentfile.c:16461)
StopIteration

Note how the second iterator stops as the file pointer has moved to chr2. The correct way to work with multiple iterators is:

samfile = pysam.AlignmentFile("pysam_ex1.bam", "rb")

iter1 = samfile.fetch("chr1", all)
print (iter1.next().reference_id)
iter2 = samfile.fetch("chr2")
print (iter2.next().reference_id)
print (iter1.next().reference_id)

Here, the output is:

0
1
0

The reason for this behaviour is that every iterator needs to keep track of its current position in the file. Within pysam, each opened file can only keep track of one file position and hence there can only be one iterator per file. Using the option mulitple_iterators=True will return an iterator within a newly opened file. This iterator will not interfere with existing iterators as it has its own file handle associated with it.

Note that re-opening files incurs a performance penalty which can become severe when calling fetch() often. Thus, multiple_iterators is set to False by default.

AlignmentFile.fetch does not show unmapped reads

fetch() will only iterate over alignments in the SAM/BAM file. The following thus always works:

bf = pysam.AlignemFile(fname, "rb")
for r in bf.fetch():
    assert not r.is_unmapped

If the SAM/BAM file contains unaligned reads, they can be included in the iteration by adding the until_eof=True flag:

bf = pysam.AlignemFile(fname, "rb")
for r in bf.fetch(until_eof=True):
    if r.is_unmapped:
        print ("read is unmapped")

I can’t call AlignmentFile.fetch on a file without index

fetch() requires an index when iterating over a SAM/BAM file. To iterate over a file without index, use the ``until_eof=True`:

bf = pysam.AlignemFile(fname, "rb")
for r in bf.fetch(until_eof=True):
    print (r)

BAM files with a large number of reference sequences are slow

If you have many reference sequences in a bam file, the following might be slow:

track = pysam.AlignmentFile(fname, "rb")
for aln in track.fetch():
    pass

The reason is that track.fetch() will iterate through the bam file for each reference sequence in the order as it is defined in the header. This might require a lot of jumping around in the file. To avoid this, use:

track = pysam.AlignmentFile(fname, "rb")
for aln in track.fetch(until_eof=True):
    pass

This will iterate through reads as they appear in the file.

Weirdness with spliced reads in samfile.pileup(chr,start,end) given spliced alignments from an RNA-seq bam file

Spliced reads are reported within samfile.pileup. To ignore these in your analysis, test the flags is_del == True and indel=0 in the PileupRead object.

I can’t edit quality scores in place

Editing reads in-place generally works, though there is some quirk to be aware of. Assigning to AlignedRead.seq will invalidate any quality scores in AlignedRead.qual. The reason is that samtools manages the memory of the sequence and quality scores together and thus requires them to always be of the same length or 0.

Thus, to in-place edit the sequence and quality scores, copies of the quality scores need to be taken. Consider trimming for example:

q = read.qual
read.seq = read.seq[5:10]
read.qual = q[5:10]

Why is there no SNPCaller class anymore?

SNP calling is highly complex and heavily parameterized. There was a danger that the pysam implementations might show different behaviour from the samtools implementation, which would have caused a lot of confusion.

The best way to use samtools SNP calling from python is to use the pysam.mpileup() command and parse the output directly.

I get an error ‘PileupProxy accessed after iterator finished’

Pysam works by providing proxy objects to objects defined within the C-samtools package. Thus, some attention must be paid at the lifetime of objects. The following to code snippets will cause an error:

s = AlignmentFile('ex1.bam')
for p in s.pileup('chr1', 1000,1010):
    pass

for pp in p.pileups:
    print pp

The iteration has finished, thus the contents of p are invalid. A variation of this:

p = next(AlignmentFile('ex1.bam').pileup('chr1', 1000, 1010))
for pp in p.pileups:
    print pp

Again, the iteration finishes as the temporary iterator created by pileup goes out of scope. The solution is to keep a handle to the iterator that remains alive:

i = AlignmentFile('ex1.bam').pileup('chr1', 1000, 1010)
p = next(i)
for pp in p.pileups:
    print pp

Pysam won’t compile

Compiling pysam can be tricky as there are numerous variables that differ between build environments such as OS, version, python version, and compiler. It is difficult to build software that build cleanly on all systems and the process might fail. Please see the pysam user group for common issues.

If there is a build issue, read the generated output carefully - generally the cause of the problem is among the first errors to be reported. For example, you will need to have the development version of python installed that includes the header files such as Python.h. If that file is missing, the compiler will report this at the very top of its error messages but will follow it with any unknown function or variable definition it encounters later on.

A general advice is to always use the latest version on python and cython when building pysam. There are some known incompatibilities:

  • Python 3.4 requires cython 0.20.2 or later (see here)

Developer’s guide

Code organization

The top level directory is organized in the following directories:

pysam
Code specific to pysam
doc

The documentation. To build the latest documention type:

make -C doc html
tests
Code and data for testing
htslib
Source code from htslib shipped with pysam. See setup.py about importing.
samtools
Source code from csamtools shipped with pysam. See setup.py about importing.

Importing new versions of htslib and samtools

See instructions in setup.py to import the latest version of htslib and samtools.

Unit testing

Unit tests are in the tests directory. To run all unit tests, run:

nosetests -s -v tests

Note to use the -s/--nocapture option to prevent nosetests from captpuring standard output.

Contributors

Please see github for a list of all contributors:

https://github.com/pysam-developers/pysam/graphs/contributors

Many thanks to all contributors for helping in making pysam useful.

Release notes

Release 0.11.2.2

Bugfix release to address two issues:

  • Changes in 0.11.2.1 broke the GTF/GFF3 parser. Corrected and more tests have been added.
  • [#479] Correct VariantRecord edge cases described in issue

Release 0.11.2.1

Release to fix release tar-ball containing 0.11.1 pre-compiled C-files.

Release 0.11.2

This release wraps htslib/samtools/bcfools versions 1.4.1 in response to a security fix in these libraries. Additionaly the following issues have been fixed:

  • [#452] add GFF3 support for tabix parsers
  • [#461] Multiple fixes related to VariantRecordInfo and handling of INFO/END
  • [#447] limit query name to 251 characters (only partially addresses issue)

VariantFile and related object fixes

  • Restore VariantFile.__dealloc__
  • Correct handling of bcf_str_missing in bcf_array_to_object and bcf_object_to_array
  • Added update() and pop() methods to some dict-like proxy objects
  • scalar INFO entries could not be set again after being deleted
  • VariantRecordInfo.__delitem__ now allows unset flags to be deleted without raising a KeyError
  • Multiple other fixes for VariantRecordInfo methods
  • INFO/END is now accessible only via VariantRecord.stop and VariantRecord.rlen. Even if present behind the scenes, it is no longer accessible via VariantRecordInfo.
  • Add argument to issue a warning instead of an exception if input appears to be truncated

Other features and fixes:

  • Make AlignmentFile __dealloc__ and close more stringent
  • Add argument AlignmentFile to issue a warning instead of an exception if input appears to be truncated

Release 0.11.1

Bugfix release

  • [#440] add deprecated ‘always’ option to infer_query_length for backwards compatibility.

Release 0.11.0

This release wraps the latest versions of htslib/samtools/bcftools and implements a few bugfixes.

  • [#413] Wrap HTSlib/Samtools/BCFtools 1.4
  • [#422] Fix missing pysam.sort.usage() message
  • [#411] Fix BGZfile initialization bug
  • [#412] Add seek support for BGZFile
  • [#395] Make BGZfile iterable
  • [#433] Correct getQueryEnd
  • [#419] Export SAM enums such as pysam.CMATCH
  • [#415] Fix access by tid in AlignmentFile.fetch()
  • [#405] Writing SAM now outputs a header by default.
  • [#332] split infer_query_length(always) into infer_query_length and infer_read_length

Release 0.10.0

This release implements further functionality in the VariantFile API and includes several bugfixes:

  • treat special case -c option in samtools view outputs to stdout even if -o given, fixes #315
  • permit reading BAM files with CSI index, closes #370
  • raise Error if query name exceeds maximum length, fixes #373
  • new method to compute hash value for AlignedSegment
  • AlignmentFile, VariantFile and TabixFile all inherit from HTSFile
  • Avoid segfault by detecting out of range reference_id and next_reference in AlignedSegment.tostring
  • Issue #355: Implement streams using file descriptors for VariantFile
  • upgrade to htslib 1.3.2
  • fix compilation with musl libc
  • Issue #316, #360: Rename all Cython modules to have lib as a prefix
  • Issue #332, hardclipped bases in cigar included by pysam.AlignedSegment.infer_query_length()
  • Added support for Python 3.6 filename encoding protocol
  • Issue #371, fix incorrect parsing of scalar INFO and FORMAT fields in VariantRecord
  • Issue #331, fix failure in VariantFile.reset() method
  • Issue #314, add VariantHeader.new_record(), VariantFile.new_record() and VariantRecord.copy() methods to create new VariantRecord objects
  • Added VariantRecordFilter.add() method to allow setting new VariantRecord filters
  • Preliminary (potentially unsafe) support for removing and altering header metadata
  • Many minor fixes and improvements to VariantFile and related objects

Release 0.9.1

This is a bugfix release addressing some installation problems in pysam 0.9.0, in particular:

  • patch included htslib to work with older libcurl versions, fixes #262.
  • do not require cython for python 3 install, fixes #260
  • FastaFile does not accept filepath_index any more, see #270
  • add AlignedSegment.get_cigar_stats method.
  • py3 bugfix in VariantFile.subset_samples, fixes #272
  • add missing sysconfig import, fixes #278
  • do not redirect stdout, but instead write to a separately created file. This should resolve issues when pysam is used in notebooks or other environments that redirect stdout.
  • wrap htslib-1.3.1, samtools-1.3.1 and bcftools-1.3.1
  • use bgzf throughout instead of gzip
  • allow specifying a fasta reference for CRAM file when opening for both read and write, fixes #280

Release 0.9.0

Overview

The 0.9.0 release upgrades htslib to htslib 1.3 and numerous other enchancements and bugfixes. See below for a detailed list.

Htslib 1.3 comes with additional capabilities for remote file access which depend on the presence of optional system libraries. As a consequence, the installation script setup.py has become more complex. For an overview, see Installing pysam. We have tested installation on linux and OS X, but could not capture all variations. It is possible that a 0.9.1 release might follow soon addressing installation issues.

The VariantFile class provides access to vcf and bcf formatted files. The class is certainly usable and interface is reaching completion, but the API and the functionality is subject to change.

Detailed release notes

  • upgrade to htslib 1.3

  • python 3 compatibility tested throughout.

  • added a first set of bcftools commands in the pysam.bcftools submodule.

  • samtools commands are now in the pysam.samtools module. For backwards compatibility they are still imported into the pysam namespace.

  • samtools/bcftools return stdout as a single (byte) string. As output can be binary (VCF.gz, BAM) this is necessary to ensure py2/py3 compatibility. To replicate the previous behaviour in py2.7, use:

    pysam.samtools.view(self.filename).splitlines(True)

  • get_tags() returns the tag type as a character, not an integer (#214)

  • TabixFile now raises ValueError on indices created by tabix <1.0 (#206)

  • improve OSX installation and develop mode

  • FastxIterator now handles empty sequences (#204)

  • TabixFile.isremote is not TabixFile.is_remote in line with AlignmentFile

  • AlignmentFile.count() has extra optional argument read_callback

  • setup.py has been changed to:
    • install a single builtin htslib library. Previously, each pysam module contained its own version. This reduces compilation time and code bloat.
    • run configure for the builtin htslib library in order to detect optional libraries such as libcurl. Configure behaviour can be controlled by setting the environmet variable HTSLIB_CONFIGURE_OPTIONS.

  • get_reference_sequence() now returns the reference sequence and not something looking like it. This bug had effects on get_aligned_pairs(with_seq=True), see #225. If you have relied on on get_aligned_pairs(with_seq=True) in pysam-0.8.4, please check your results.

  • improved autodetection of file formats in AlignmentFile and VariantFile.

Release 0.8.4

This release contains numerous bugfixes and a first implementation of a pythonic interface to VCF/BCF files. Note that this code is still incomplete and preliminary, but does offer a nearly complete immutable Pythonic interface to VCF/BCF metadata and data with reading and writing capability.

Potential isses when upgrading from v0.8.3:

  • binary tags are now returned as python arrays

  • renamed several methods for pep8 compatibility, old names still retained for backwards compatibility, but should be considered deprecated.

    • gettid() is now get_tid()
    • getrname() is now get_reference_name()
    • parseRegion() is now parse_region()

  • some methods have changed for pep8 compatibility without the old names being present:

    • fromQualityString() is now qualitystring_to_array()
    • toQualityString() is now qualities_to_qualitystring()

  • faidx now returns strings and not binary strings in py3.

  • The cython components have been broken up into smaller files with more specific content. This will affect users using the cython interfaces.

Edited list of commit log changes:

  • fixes AlignmentFile.check_index to return True
  • add RG/PM header tag - closes #179
  • add with_seq option to get_aligned_pairs
  • use char * inside reconsituteReferenceSequence
  • add soft clipping for get_reference_sequence
  • add get_reference_sequence
  • queryEnd now computes length from cigar string if no sequence present, closes #176
  • tolerate missing space at end of gtf files, closes #162
  • do not raise Error when receiving output on stderr
  • add docu about fetching without index, closes #170
  • FastaFile and FastxFile now return strings in python3, closes #173
  • py3 compat: relative -> absolute imports.
  • add reference_name and next_reference_name attributes to AlignedSegment
  • add function signatures to cvcf cython. Added note about other VCF code.
  • add context manager functions to FastaFile
  • add reference_name and next_reference_name attributes to AlignedSegment
  • PileupColumn also gets a reference_name attribute.
  • add context manager functions to FastaFile
  • TabixFile.header for remote files raises AttributeError, fixes #157
  • add context manager interface to TabixFile, closes #165
  • change ctypedef enum to typedef enum for cython 0.23
  • add function signatures to cvcf cython, also added note about other VCF code
  • remove exception for custom upper-case header record tags.
  • rename VALID_HEADER_FIELDS to KNOWN_HEADER_FIELDS
  • fix header record tag parsing for custom tags.
  • use cython.str in count_coverage, fixes #141
  • avoid maketrans (issues with python3)
  • refactoring: AlignedSegment now in separate module
  • do not execute remote tests if URL not available
  • fix the unmapped count, incl reads with no SQ group
  • add raw output to tags
  • added write access for binary tags
  • bugfix in call to resize
  • implemented writing of binary tags from arrays
  • implemented convert_binary_tag to use arrays
  • add special cases for reads that are unmapped or whose mates are unmapped.
  • rename TabProxies to ctabixproxies
  • remove underscores from utility functions
  • move utility methods into cutils
  • remove callback argument to fetch - closes #128
  • avoid calling close in dealloc
  • add unit tests for File object opening
  • change AlignmentFile.open to filepath_or_object
  • implement copy.copy, close #65
  • add chaching of array attributes in AlignedSegment, closes #121
  • add export of Fastafile
  • remove superfluous pysam_dispatch
  • use persist option in FastqFile
  • get_tag: expose tag type if requested with with_value_type
  • fix to allow reading vcf record info via tabix-based vcf reader
  • add pFastqProxy and pFastqFile objects to make it possible to work with multiple fastq records per file handle, unlike FastqProxy/FastqFile.
  • release GIL around htslib IO operations
  • More work on read/write support, API improvements
  • add phased property on VariantRecordSample
  • add mutable properties to VariantRecord
  • BCF fixes and start of read/write support
  • VariantHeaderRecord objects now act like mappings for attributes.
  • add VariantHeader.alts dict from alt ID->Record.
  • Bug fix to strong representation of structured header records.
  • VariantHeader is now mutable

Release 0.8.3

  • samtools command now accept the “catch_stdout” option.
  • get_aligned_pairs now works for soft-clipped reads.
  • query_position is now None when a PileupRead is not aligned to a particular position.
  • AlignedSegments are now comparable and hashable.

Release 0.8.2.1

  • Installation bugfix release.

Release 0.8.2

  • Pysam now wraps htslib 1.2.1 and samtools version 1.2.
  • Added CRAM file support to pysam.
  • New alignment info interface.
    • opt() and setTag are deprecated, use get_tag() and set_tag() instead.
    • added has_tag()
    • tags is deprecated, use get_tags() and set_tags() instead.
  • FastqFile is now FastxFile to reflect that the latter permits iteration over both fastq- and fasta-formatted files.
  • A Cython wrapper for htslib VCF/BCF reader/writer. The wrapper provides a nearly complete Pythonic interface to VCF/BCF metadata with reading and writing capability. However, the interface is still incomplete and preliminary and lacks capability to mutate the resulting data.

Release 0.8.1

  • Pysam now wraps htslib and samtools versions 1.1.
  • Bugfixes, most notable: * issue #43: uncompressed BAM output * issue #42: skip tests requiring network if none available * issue #19: multiple iterators can now be made to work on the same tabix file * issue #24: All strings returned from/passed to the pysam API are now unicode in python 3 * issue #5: type guessing for lists of integers fixed
  • API changes for consistency. The old API is still present, but deprecated. In particular:
    • Tabixfile -> TabixFile
    • Fastafile -> FastaFile
    • Fastqfile -> FastqFile
    • Samfile -> AlignmentFile
    • AlignedRead -> AlignedSegment
      • qname -> query_name
      • tid -> reference_id
      • pos -> reference_start
      • mapq -> mapping_quality
      • rnext -> next_reference_id
      • pnext -> next_reference_start
      • cigar -> cigartuples
      • cigarstring -> cigarstring
      • tlen -> template_length
      • seq -> query_sequence
      • qual -> query_qualities, now returns array
      • qqual -> query_alignment_qualities, now returns array
      • tags -> tags
      • alen -> reference_length, reference is always “alignment”, so removed
      • aend -> reference_end
      • rlen -> query_length
      • query -> query_alignment_sequence
      • qstart -> query_alignment_start
      • qend -> query_alignment_end
      • qlen -> query_alignment_length
      • mrnm -> next_reference_id
      • mpos -> next_reference_start
      • rname -> reference_id
      • isize -> template_length
      • blocks -> get_blocks()
      • aligned_pairs -> get_aligned_pairs()
      • inferred_length -> infer_query_length()
      • positions -> get_reference_positions()
      • overlap() -> get_overlap()
    • All strings are now passed to or received from the pysam API as strings, no more bytes.
Other changes:
  • AlignmentFile.fetch(reopen) option is now multiple_iterators. The default changed to not reopen a file unless requested by the user.
  • FastaFile.getReferenceLength is now FastaFile.get_reference_length

Backwards incompatible changes

  • Empty cigarstring now returns None (intstead of ‘’)
  • Empty cigar now returns None (instead of [])
  • When using the extension classes in cython modules, AlignedRead needs to be substituted with AlignedSegment.
  • fancy_str() has been removed
  • qual, qqual now return arrays

Release 0.8.0

  • Disabled features
    • IteratorColumn.setMask() disabled as htslib does not implement this functionality?
  • Not implemented yet:
    • reading SAM files without header

Tabix files between version 0.7.8 and 0.8.0 are not compatible and need to be re-indexed.

While version 0.7.8 and 0.8.0 should be mostly compatible, there are some notable exceptions:

  • tabix iterators will fail if there are comments in the middle or the end of a file.
  • tabix raises always ValueError for invalid intervals. Previously, different types of errors were raised (KeyError, IndexError, ValueError) depending on the type of invalid intervals (missing chromosome, out-of-range, malformatted interval).

Release 0.7.8

  • added AlignedRead.setTag method
  • added AlignedRead.blocks
  • unsetting CIGAR strings is now possible
  • empty CIGAR string returns empty list
  • added reopen flag to Samfile.fetch()
  • various bugfixes

Release 0.7.7

  • added Fastafile.references, .nreferences and .lengths
  • tabix_iterator now uses kseq.h for python 2.7

Release 0.7.6

  • added inferred_length property
  • issue 122: MACOSX getline missing, now it works?
  • seq and qual can be set None
  • added Fastqfile

Release 0.7.5

  • switch to samtools 0.1.19
  • issue 122: MACOSX getline missing
  • issue 130: clean up tempfiles
  • various other bugfixes

Release 0.7.4

  • further bugfixes to setup.py and package layout

Release 0.7.3

  • further bugfixes to setup.py
  • upgraded distribute_setup.py to 0.6.34

Release 0.7.2

  • bugfix in installer - failed when cython not present
  • changed installation locations of shared libraries

Release 0.7.1

  • bugfix: missing PP tag PG records in header
  • added pre-built .c files to distribution

Release 0.7

  • switch to tabix 0.2.6
  • added cigarstring field
  • python3 compatibility
  • added B tag handling
  • added check_sq and check_header options to Samfile.__init__
  • added lazy GTF parsing to tabix
  • reworked support for VCF format parsing
  • bugfixes

Release 0.6

  • switch to samtools 0.1.18
  • various bugfixes
  • removed references to deprecated ‘samtools pileup’ functionality
  • AlignedRead.tags now returns an empty list if there are no tags.
  • added pnext, rnext and tlen

Release 0.5

  • switch to samtools 0.1.16 and tabix 0.2.5
  • improved tabix parsing, added vcf support
  • re-organized code to permit linking against pysam
  • various bugfixes
  • added Samfile.positions and Samfile.overlap

Release 0.4

  • switch to samtools 0.1.12a and tabix 0.2.3
  • added snp and indel calling.
  • switch from pyrex to cython
  • changed handling of samtools stderr
  • various bugfixes
  • added Samfile.count and Samfile.mate
  • deprecated AlignedRead.rname, added AlignedRead.tid

Release 0.3

  • switch to samtools 0.1.8
  • added support for tabix files
  • numerous bugfixes including
  • permit simultaneous iterators on the same file
  • working access to remote files

Glossary

BAM
Binary SAM format. BAM files are binary formatted, indexed and allow random access.
BCF
Binary VCF
bgzip
Utility in the htslib package to block compress genomic data files.
cigar
An alignment format string. In the python API, the cigar alignment is presented as a list of tuples (operation,length). For example, the tuple [ (0,3), (1,5), (0,2) ] refers to an alignment with 3 matches, 5 insertions and another 2 matches.
column
Reads that are aligned to a base in the reference sequence.
csamtools
The samtools C-API.
faidx
Utility in the samtools package to index fasta formatted files.
fetching
Retrieving all mapped reads mapped to a region.
hard clipping
hard clipped
In hard clipped reads, part of the sequence has been removed prior to alignment. That only a subsequence is aligend might be recorded in the cigar alignment, but the removed sequence will not be part of the alignment record, in contrast to soft clipped reads.
pileup
Pileup
Reference
The sequence that a tid refers to. For example chr1, contig123.
region
A genomic region, stated relative to a reference sequence. A region consists of reference name (‘chr1’), start (10000), and end (20000). Start and end can be omitted for regions spanning a whole chromosome. If end is missing, the region will span from start to the end of the chromosome. Within pysam, coordinates are 0-based, half-open intervals, i.e., the position 10,000 is part of the interval, but 20,000 is not. An exception are samtools compatible region strings such as ‘chr1:10000:20000’, which are closed, i.e., both positions 10,000 and 20,000 are part of the interval.
SAM
A textual format for storing genomic alignment information.
sam file
A file containing aligned reads. The sam file can either be a BAM file or a TAM file.
samtools
The samtools package.
soft clipping
soft clipped
In alignments with soft clipping part of the query sequence are not aligned. The unaligned query sequence is still part of the alignment record. This is in difference to hard clipped reads.
tabix
Utility in the htslib package to index bgzip compressed files.
tabix file
A sorted, compressed and indexed tab-separated file created by the command line tool tabix or the commands tabix_compress() and tabix_index(). The file is indexed by chromosomal coordinates.
tabix row
A row in a tabix file. Fields within a row are tab-separated.
TAM
Text SAM file. TAM files are human readable files of tab-separated fields. TAM files do not allow random access.
target
The sequence that a read has been aligned to. Target sequences have bot a numerical identifier (tid) and an alphanumeric name (Reference).
tid
The target id. The target id is 0 or a positive integer mapping to entries within the sequence dictionary in the header section of a TAM file or BAM file.
VCF
Variant call format

Indices and tables

Contents:

References

[Li2009]The Sequence Alignment/Map format and SAMtools. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R; 1000 Genome Project Data Processing Subgroup. Bioinformatics. 2009 Aug 15;25(16):2078-9. Epub 2009 Jun 8. PMID: 19505943

See also

Information about htslib
http://www.htslib.org
The samtools homepage
http://samtools.sourceforge.net
The cython C-extensions for python
http://cython.org/
The python language
http://www.python.org