BAM

Functions

• Read bam file, stats the bamfile (reads, mapping ratio…);
• Get the depth for a genomic region (and visualization);
• Get the reads overlapped with a genomic region;

Col	Field	Type	Brief Description
1	QNAME	String	Query template NAME
2	FLAG	Int bitwise	FLAG
3	RNAME	String	References sequence NAME
4	POS	Int	1- based leftmost mapping POSition
5	MAPQ	Int	MAPping Quality
6	CIGAR	String	CIGAR String
7	RNEXT	String	Ref. name of the mate/next read
8	PNEXT	Int	Position of the mate/next read
9	TLEN	Int	observed Template LENgth
10	SEQ	String	segment SEQuence
11	QUAL	String	ASCII of Phred-scaled base QUALity+33

Design

Most of the function develop based on “samtools”. The version should be >=1.3.0

• samtools depth: to get the coverage depth;
• samtools view chrN:start-end : to get the overlapped reads;

Class

class baseq.bam.BAMTYPE(path, bedfile='')

BAM File Handler, Based on samtools. While initiate, it read the path using samtools and will parse the headers.

Usage:

• Stats on enrichment quality.

get_columns(rows=10000, colIdx=6)

Read the bamfile using samtools, get the infors in the column<colIDx> and first <rows> of Rows. The columns of bam files are:

1. header
2. flags
3. chromosome
4. start
5. mapping quality
6. cigar

The colIdx start from 1.

BAMTYPE(path).get_columns(1000, 3)
# ['chr1', 'chr1', ...]

get_reads(chr, start, end)

Return The Reads that overlaps with region chrN:start-end.

• Skip reads contains “N” cigar.

read_counts(chr, star, end)

Todo:

• For module TODOs

region_bed_depth(bedfile)

The depth of regions in an bed file.

region_depth(chr, start, end, all=False)

Get the depth coverage of bases in the region. It will suitable for chromesome name like “chr1” and “1”.

Parameters:all – Shall the bases with zero coverge be returned.

Usage:

BAMTYPE(path).region_depth("chr1", 1000, 2000, all=True)
`return depth list [0,1,1,1,2,2,2,3,0]`

stats_bam()

Read the bampath.stat, if not exists, perform the samtools flagstat The results will be:

1. self.reads_total
2. self.reads_mapped
3. self.mapping_ratio

stats_bases()

Stats on the mean match length for the top 100K reads in the bam file

stats_duplicates()

Stats Duplication Rates from the top 1M reads; The duplication should be reflected in the flag

stats_region_coverage(numbers=1000)

Check the enrichment quality.

• Require a bedfile while initiating the class
• Select <numbers> regions randomly
• Use multithread pool to get the coverage depth of the regions
• Stats on the ratio of 10X, 30X, 50X and 100X bases

Usage:

BAMTYPE("sample.bam", "panel.bed").stats_region_coverage(1000)
The results will be save in object properies:
self.mean_depth/self.pct_10X/..