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!
Unconfigured Ad
Collapse
X
-
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:
And then either something likeCode:bam1=mapped_reads.bam bam2=intergenic_reads.bam annotation=annotated_genes.bed bedtools intersect -v -abam $bam1 -b $annotation > $bam2 samtools index $bam2
Or simplyCode: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
You might also be interested in how close your reads are from annotated exons. Have a look at "bedtools closest".Code:samtools idxstats $bam2
Latest Articles
Collapse
-
by SEQadmin2
NGS has revolutionized clinical microbiology by offering new ways to identify and surveil pathogens without prior knowledge of the target. One popular approach is 16S rRNA and ITS amplicon sequencing, which targets specific microbial markers. But studies are increasingly incorporating shotgun metagenomics, a technique that sequences all DNA from a sample without targeting specific microbial markers. This approach allows more detailed taxonomic classification, detection...-
Channel: Articles
Today, 06:46 AM -
-
by SEQadmin2
Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?
Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating...-
Channel: Articles
10-14-2026, 09:55 AM -
ad_right_rmr
Collapse
News
Collapse
| Topics | Statistics | Last Post | ||
|---|---|---|---|---|
|
Genome Sequencing Reveals Large, Repeat-Rich DNA in Trapdoor Spider Named for Stephen Colbert
by SEQadmin2
Started by SEQadmin2, 10-28-2026, 09:57 AM
|
0 responses
24 views
0 reactions
|
Last Post
by SEQadmin2
10-28-2026, 09:57 AM
|
||
|
Started by SEQadmin2, 10-28-2026, 09:51 AM
|
0 responses
15 views
0 reactions
|
Last Post
by SEQadmin2
10-28-2026, 09:51 AM
|
||
|
Started by SEQadmin2, 10-22-2026, 11:13 AM
|
0 responses
68 views
0 reactions
|
Last Post
by SEQadmin2
10-22-2026, 11:13 AM
|
||
|
Started by SEQadmin2, 10-22-2026, 10:48 AM
|
0 responses
48 views
0 reactions
|
Last Post
by SEQadmin2
10-22-2026, 10:48 AM
|
Comment