I have data from an experiment which is looking into differential expression of small RNA. It seems that a fraction of the reads are mapped outside of the annotated regions of the mouse genome (as listed in the Ensemble GTF file). To be honest, I am not expecting to find new genes in such a popular model organism but I am still curious where these reads map. I would like to produce statistics for each chromosome listing the number of reads that are mapped outside of the annotated regions. What's the easiest way to produce such statistics? I am using bowtie1, samtools and htseq-count in my current pipeline but so far I have always limited my analysis to the annotated regions so I am not sure how to best approach this - any advice is most welcome!
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If you have read alignments in bam format on the one hand and a gene annotation in gtf/gff/bed format on the other hand it should be simple to compare both with bedtools.
For instance something like "bedtools intersect -v -abam mapped_reads.bam -b exons.bed" should give you the reads that do not intersect any annotated exon (you can use entire gene regions if you prefer to discard intronic reads). Pipe this to "samtools view -c -" to get the number of reads.
More precisely:
Code:bam1=mapped_reads.bam bam2=intergenic_reads.bam annotation=annotated_genes.bed bedtools intersect -v -abam $bam1 -b $annotation > $bam2 samtools index $bam2
Code:for chr in `cat list_of_chromosomes.txt` ; do N=`samtools view -c $bam1 $chr` ; n=` samtools view -c $bam2 $chr` ; echo $chr $n $N ; done
Code:samtools idxstats $bam2
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