count how many mapped reads in a bam file

I wanted to count how many mapped reads are in a ChIP-seq bam file downloaded from UCSC ECODE project. http://genome.ucsc.edu/ENCODE/downloads.html

A quick google search:
http://left.subtree.org/
and http://seqanswers.com/forums/showthread.php?t=891

The output from short read aligners like Bowtie and BWA is commonly stored in SAM/BAM format. When presented with one of these files a common first task is to calculate the total number of alignments (reads) captured in the file. In this post I show some examples for finding the total number of reads using samtools and directly from Java code. For the examples below, I use the HG00173.chrom11 BAM file from the 1000 genomes project which can be downloaded here.

First, we look at using the samtools command directly. One way to get the total number of alignments is to simply dump the entire SAM file and tell samtools to count instead of print (-c option):

1 2	$ samtools view -c HG00173.chrom11.ILLUMINA.bwa.FIN.low_coverage.20111114.bam 5218322

If we’re only interested in counting the total number of mapped reads we can add the -F 4 flag. Alternativley, we can count only the unmapped reads with -f 4:

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# Mapped reads only $ samtools view -c -F 4 HG00173.chrom11.ILLUMINA.bwa.FIN.low_coverage.20111114.bam 5068340 # Unmapped reads only $ samtools view -c -f 4 HG00173.chrom11.ILLUMINA.bwa.FIN.low_coverage.20111114.bam 149982

To understand how this works we first need to inspect the SAM format. The SAM format includes a bitwise FLAG field described here. The -f/-F options to the samtools command allow us to query based on the presense/absence of bits in the FLAG field. So -f 4 only output alignments that are unmapped (flag 0×0004 is set) and -F 4 only output alignments that are not unmapped (i.e. flag 0×0004 is not set), hence these would only include mapped alignments.

An example for paired end reads you could do the following. To count the number of reads having both itself and it’s mate mapped:

1 2	$ samtools view -c -f 1 -F 12 HG00173.chrom11.ILLUMINA.bwa.FIN.low_coverage.20111114.bam 4906035

The -f 1 switch only includes reads that are paired in sequencing and -F 12 only includes reads that are notunmapped (flag 0×0004 is not set) and where the mate is not unmapped (flag 0×0008 is not set). Here we add 0x0004 + 0x0008 = 12 and use the -F (bits not set), meaning you want to include all reads where neither flag 0×0004 or 0×0008 is set. For help understanding the values for the SAM FLAG field there’s a handy web tool here.

There’s also a nice command included in samtools called flagstat which computes various summary statistics. However, I wasn’t able to find much documentation describing the output and it’s not mentioned anywhere in the man page. This post examines the C code for the flagstat command which provides some insight into the output.

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$ samtools flagstat HG00173.chrom11.ILLUMINA.bwa.FIN.low_coverage.20111114.bam 5218322 + 0 in total (QC-passed reads + QC-failed reads) 273531 + 0 duplicates 5068340 + 0 mapped (97.13%:-nan%) 5205999 + 0 paired in sequencing 2603248 + 0 read1 2602751 + 0 read2 4881994 + 0 properly paired (93.78%:-nan%) 4906035 + 0 with itself and mate mapped 149982 + 0 singletons (2.88%:-nan%) 19869 + 0 with mate mapped to a different chr 15271 + 0 with mate mapped to a different chr (mapQ>=5)

So, samtools flagstat  is what I need.


tommy@tommy-ThinkPad-T420:~/Desktop$ time samtools flagstat Mcf7Ctcf.sorted.bam 
20769652 + 0 in total (QC-passed reads + QC-failed reads)
0 + 0 duplicates
20769652 + 0 mapped (100.00%:-nan%)
0 + 0 paired in sequencing
0 + 0 read1
0 + 0 read2
0 + 0 properly paired (-nan%:-nan%)
0 + 0 with itself and mate mapped
0 + 0 singletons (-nan%:-nan%)
0 + 0 with mate mapped to a different chr
0 + 0 with mate mapped to a different chr (mapQ>=5)

real 0m12.472s
user 0m11.237s
sys 0m0.384s

it is pretty fast.  with 12 seconds it finished counting a bam file with 20 million reads.

I used to use HTSeq python package http://www-huber.embl.de/users/anders/HTSeq/doc/overview.html
 to count the mapped reads, but it is much slower (several mins to count the same file) than samtools.


def aligned_counts(ifile1):
    '''count how many alignments are aligned back to genome, ifile1 is a sorted bam file'''
    import HTSeq
    sortedbamfile= HTSeq.BAM_Reader(ifile1)
    aligned_counts=0
    unaligned_counts=0
    for almnt in sortedbamfile:
        if almnt.aligned:
            aligned_counts+= 1
        else:
            unaligned_counts+=1
    print "number of aligned tags of %s is %d " % (ifile1, aligned_counts)
    print "number of unaligned tags of %s is %d "% (ifile1, unaligned_counts)
    return aligned_counts

Again, I am happy with the existing tools. Do not re-invent the wheels !