Hi all,
I am mapping small RNA sequencing reads with bowtie1.2.2 to a locus that encodes a direct repeat with the exactly(!) the same sequence repeated 19 times. I don't allow mismatches, and ask to get back only one alignment:
bowtie index clippedreads.fq --best --strata -M 1 -v 0 -S | \
samtools view -Sb -F 4 - |\
samtools sort - -o outfile.bam
(or alternatively --best -k 1 -v 0; however, it does not really make a difference in my hands)
A couple of thousand reads are mapping to that locus (all these reads have the same sequence of course), and based on the bowtie1 manual I would assume they are randomly (and roughly equally) distributed across the 19 repeat units. However, what I get is one or two of the repeat units are highly covered, and the rest is distributed as expected (see picture):
Weirdly, the peak shifts with different libraries, but is otherwise nicely reproducible.
I was wondering what is going on, why the repeat units are not equally covered, or how this can be handled?
Thanks a ton! Any suggestion is highly appreciated.
I am mapping small RNA sequencing reads with bowtie1.2.2 to a locus that encodes a direct repeat with the exactly(!) the same sequence repeated 19 times. I don't allow mismatches, and ask to get back only one alignment:
bowtie index clippedreads.fq --best --strata -M 1 -v 0 -S | \
samtools view -Sb -F 4 - |\
samtools sort - -o outfile.bam
(or alternatively --best -k 1 -v 0; however, it does not really make a difference in my hands)
A couple of thousand reads are mapping to that locus (all these reads have the same sequence of course), and based on the bowtie1 manual I would assume they are randomly (and roughly equally) distributed across the 19 repeat units. However, what I get is one or two of the repeat units are highly covered, and the rest is distributed as expected (see picture):
Weirdly, the peak shifts with different libraries, but is otherwise nicely reproducible.
I was wondering what is going on, why the repeat units are not equally covered, or how this can be handled?
Thanks a ton! Any suggestion is highly appreciated.
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