coalispr.bedgraph_analyze.process_bamdata¶

Module to count bam files based on specification of aligned reads.

Attributes¶

logger

Classes¶

`Bam_collector`	Class to keep track of bam files.
`Total_counter`
`Read_checker`	Class to store outcome of cigar and other read checks.
`Bam_countprocessor`
`Bedgraphs_from_unselected`	Class to create bedgraphs from new bam-files with unselected reads.

Functions¶

`total_raw_counts`(tagBam, stranded[, force])	Obtain total mapped reads and unmapped reads from alignments.
`count_folder`(kind, bam, segments, overmax, maincut, ...)	Return folder with stored count files
`has_been_counted`(typeofcount, kind[, folder])	Check whether count files have been created.
`process_bam_files`(bins, kind, writebam, force, cigchk, ...)	Obtain count data from available bam-alignment files. When possible,
`process_reads_for_region`(samples, chrnam, region, ...)	Obtain read-length data for a particular region on chromosome chrnam

Module Contents¶

coalispr.bedgraph_analyze.process_bamdata.logger¶

class coalispr.bedgraph_analyze.process_bamdata.Bam_collector¶

Class to keep track of bam files.

bamkeys¶

nodiscards_keys¶

bamfiles¶

tag¶

bamkeys: list¶

nodiscards_keys: list¶

bamfiles: dict¶

tag: str¶

classmethod collect_bamfiles(tag=TAGBAM, src_dir=SRCDIR, ndirlevels=SRCNDIRLEVEL)¶

Retrieve all bam-file names for counting aligned reads.

These are marked by SAMBAM.

Parameters:

tag (str (default: TAGBAM)) – Type of aligned-reads (collapsed or uncollapsed).
src_dir (Path (default: SRCDIR)) – Path to folder with sequencing data incl. bamfiles.
ndirlevels (int (default: SRCNDIRLEVEL)) – Number of subdirectories to traverse from SRC directory to get to bamfiles.

Returns:

Dictionary of sample (SHORT) names and paths to associated SAMBAM-files.

Return type:

dict

classmethod get_bamfiles(tag)¶

classmethod num_counted_libs(plusdiscards=True)¶: Retrieve number of counted libraries from number counted bam-files.

classmethod keys_counted_libs(plusdiscards=True)¶: Retrieve keys linked to counted bam-files.

coalispr.bedgraph_analyze.process_bamdata.total_raw_counts(tagBam, stranded, force=False)¶

Obtain total mapped reads and unmapped reads from alignments.

Parameters:

tagBam (str) – Determines type of reads counted, TAGUNCOLL, or TAGCOLL.
stranded (bool) – Flag to output total counts for each strand.
force (bool) – Flag to redo counting (while backing up previous results).

Returns:

A text file with tab-separated columns giving total input numbers for all experiments.

Return type:

A TSV file

class coalispr.bedgraph_analyze.process_bamdata.Total_counter¶

samheader_counters: list¶

unmapped_counters: list¶

bams: dict¶

tagBam: str¶

tsvpath: pathlib.Path¶

filepath: pathlib.Path¶

keys: list¶

unmap_in_sam: bool¶

suffuncs¶

totalfram: pandas.DataFrame¶

classmethod init_raw_count(tagBam, stranded, force)¶: Set up common variables.

classmethod get_samheader_counts(key)¶: Get counts from SAM header or from line counting in BAM file.

classmethod process_samheader_counts()¶: Create dataframe from obtained counts.

classmethod count_unmapped_lines(key)¶: Count lines in file with unmapped reads, put apart during alignment.

classmethod external_unmapped_counts()¶: Obtain counts for unmapped reads put aside in UNMAPPEDFIL, another file than the BAM alignment file.

classmethod process_external_unmapped()¶: Process counts obtained for UNMAPPEDFIL reads.

classmethod process_totalfram()¶: Save dataframe with all counts to file.

classmethod get_raw_counts(tagBam=None, stranded=False, force=False)¶

coalispr.bedgraph_analyze.process_bamdata.count_folder(kind, bam, segments, overmax, maincut, usegaps)¶: Return folder with stored count files

coalispr.bedgraph_analyze.process_bamdata.has_been_counted(typeofcount, kind, folder=None)¶

Check whether count files have been created.

Parameters:

typeofcount (str) – Pattern to find specific files
kind (str) – Select kind of reads that have been counted, either SPECIFIC or UNSPECIFIC

Return type:

boolean to indicate count file is present (True) or not (False)

class coalispr.bedgraph_analyze.process_bamdata.Read_checker¶

Class to store outcome of cigar and other read checks.

unfit_read¶

Type:: fcie

nomis¶

Indicates number of mismatches (default: NRMISM)

Type:: int

okintrons¶

Type:: list

unfit_read = None¶

nomis: int¶

okintrons: list¶

classmethod make_cigarcheck(cigchk, nomis=NRMISM)¶

Take cigar items as marked by ‘cigartuples; cigarstring; <meaning>’:

0;M <match>,
1;I <insertion>,
2;D <deletion>,
3;N <skipped>,

which are standard (the other accepted cigar items:

4;S <soft clip>,
5;H <hard clip>,
6;P <padding>,
7;= <sequence match>,
8;X <sequence mismatch, substitution>

are indirectly used here. Skip if alignment is dubious; for short SE sequences only accept matches (0;M) and gaps (3;N); for reads from UV-treated samples accept a point-deletion (2;D)

Parameters:

cigchk (str (from CIGARCHK, either CIGPD or CIGFM)) – Defines function to use for checking a read.
nomis (int (default: NRMISM))

classmethod ok_read(read, intronchk=True)¶

Check cigar and number of tolerated mismatches for each read.

Parameters:

read (pysam.AlignedSegment) – Input for obtaining tuples describing the cigar string of an aligned read, number of mismatches and introns.
intronchk (bool) – Check for introns and gather their lengths (or not).

Return type:

True or False and sets list of intron-lengths for valid introns

classmethod hitidx(hit_idx, beancounter)¶: Check hit-index for read as defined in alignment file.

classmethod ok_strand(read, strand)¶

Check strand of read for inclusion in counts

Parameters:

read (pysam.AlignedSegment) – Input for obtaining tuples describing the cigar string of an aligned read, number of mismatches and introns.
strand (str) – One of COMBI, PLUS or MINUS; for selecting sense/antisense in defined sections (for which the MUNR and CORB properties are neither set nor applicable).

Return type:

True or False

class coalispr.bedgraph_analyze.process_bamdata.Bam_countprocessor¶

bampath: pathlib.Path¶

bampeak: tuple¶

bams: dict¶

bamstart: int¶

beancollector: coalispr.bedgraph_analyze.bam_keys_collators.Bam_samples_collator¶

collected_counters: list¶

comparereads: list¶

countselect: bool¶

bins: int¶

cols: list¶

force: bool¶

gap: int¶

has_chrxtra: bool¶

keys: list¶

kind: str¶

region: str¶

segs: dict¶

selectbam: pysam.AlignmentFile¶

strand: str¶

TEST: bool¶

tsvpath: pathlib.Path¶

writebam: bool¶

cigchk = 'fullmatch'¶

maincut = 1¶

nomis = 0¶

tresh = 5¶

classmethod run_all_bamcount_processes(bins, kind, writebam, force, cigchk, nomis)¶: Steps to obtain counts from all bam files, by sequential or multi- processing. Inner function needed to get run-time counting.

classmethod process_bamfile(key)¶: Multiprocess this part.

classmethod check_bam_file(inbam)¶

classmethod check_mulmap()¶

classmethod init_counting(bins, kind, writebam, force, cigchk, nomis)¶

classmethod run_region_count_processes(samples, chrnam, region, strand, comparereads, cigchk, nomis)¶

coalispr.bedgraph_analyze.process_bamdata.process_bam_files(bins, kind, writebam, force, cigchk, nomis)¶

Obtain count data from available bam-alignment files. When possible, uses multi-processing, otherwise sequential counting of files.

Parameters:

bins (int) – Number of bins counts are split over (default BINS)
kind (str) – Kind of read, SPECIFIC or UNSPECIFIC
writebam (bool) – Save UNSELECTED UNSPECIFIC reads in bam-alignment files for inclusion to showgraphs as a separate group of reads.
force (bool) – Allow recounting samples, backup existing count files.
cigchk (str) – From cigar string CIGARCHK, either CIGPD or CIGFM, defines function to use for checking a read.
nomis (int) – Number of tolerated substitutions, default: NRMISM.

coalispr.bedgraph_analyze.process_bamdata.process_reads_for_region(samples, chrnam, region, strand, comparereads, cigchk, nomis)¶

Obtain read-length data for a particular region on chromosome chrnam for given samples.

Parameters:

samples (list) – List of short names to retrieve bamfiles with alignment data for.
chrnam (str) – Name of chromosome to retrieve region from.
region (tuple) – Tuple with coordinates for chromosomal region to retrieve counts for.
strand (str) – One of COMBI, PLUS or MINUS; for selecting sense/antisense in defined sections (for which the MUNR and CORB properties are neither set nor applicable).
comparereads (list) – List of reads to count for comparison.
cigchk (str) – From cigar string CIGARCHK, either CIGPD or CIGFM, defines function to use for checking a read.
nomis (int) – Number of tolerated substitutions, default: NRMISM.

Returns:

output – For making graphs, a pandas.Dataframe with read counts and a list of dataframes with counts for read lengths.

Return type:

tuple

class coalispr.bedgraph_analyze.process_bamdata.Bedgraphs_from_unselected¶

Class to create bedgraphs from new bam-files with unselected reads.

Attributes:¶

bampath: Path: Path to input bam-file.

classmethod sortindex(bampath)¶

classmethod bedgraphs_from_xtra_bamdata(bampath)¶

Create bedgraph files from selected bamdata.

During specification of reads, target-like RNAs (like siRNAs) may be thrown out because of overlap with more abundant reads in the negative controls. Based on a telling determinant (like start-nucleotide and length range for siRNA) such target-like reads can be retrieved during counting of unspecified reads and copied to new bam files. Here, these reads are extracted and processed. The fraction of such target-like reads may come along by chance, and therefore could represent false positives, especially when these do not stand out for positive controls or change by interfering mutations/conditions.

Bam files need to be sorted and indexed before they can be converted to bedgraphs