Evaluate coverage of specific motifs

drea11 · 04-08-2015, 09:50 AM

Is there a method out there that would allow me to determine whether a particular sequence motif (DNA) has adequate sequencing depth of coverage across a genome? What I am interested in seeing is whether or not any specific sequence motifs are associated with decreased levels of sequencing coverage across the genome. I have illumina miseq data, and can see one of two ways of doing this. 1) I identify regions with low coverage, identify motifs within these regions that are common between all or most of these regions, then compare them to random other equally sized regions in the genome. Or 2) I randomly generate kmers across the genome, and then evaluate the sequencing coverage across these kmers and determine if any have significantly lower values than the others. I'm wondering if anyone has done this before, and whether there might be a tool that has been created to do this?
Thanks

diego diaz · 04-09-2015, 01:59 PM

This is a possible solution,

1) Create a FASTA file with your motifs.
2) Map your motifs to your reference genome (with BLAST, BLAT or even bowtie) to get motif coordinates, then, transform this coordinates into a bed file.
3) Use bedtools coverage to calculate the depth in the motif regions (Example : bedtools coverage -aBam mapping_file.bam -b motif_coords.bed)

I hope that helps !

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04-08-2015, 09:50 AM	#1
drea11 Junior Member Location: Canada Join Date: Aug 2014 Posts: 9	Evaluate coverage of specific motifs Is there a method out there that would allow me to determine whether a particular sequence motif (DNA) has adequate sequencing depth of coverage across a genome? What I am interested in seeing is whether or not any specific sequence motifs are associated with decreased levels of sequencing coverage across the genome. I have illumina miseq data, and can see one of two ways of doing this. 1) I identify regions with low coverage, identify motifs within these regions that are common between all or most of these regions, then compare them to random other equally sized regions in the genome. Or 2) I randomly generate kmers across the genome, and then evaluate the sequencing coverage across these kmers and determine if any have significantly lower values than the others. I'm wondering if anyone has done this before, and whether there might be a tool that has been created to do this? Thanks

04-09-2015, 01:59 PM	#2
diego diaz Member Location: Santiago, Chile Join Date: Oct 2013 Posts: 62	This is a possible solution, 1) Create a FASTA file with your motifs. 2) Map your motifs to your reference genome (with BLAST, BLAT or even bowtie) to get motif coordinates, then, transform this coordinates into a bed file. 3) Use bedtools coverage to calculate the depth in the motif regions (Example : bedtools coverage -aBam mapping_file.bam -b motif_coords.bed) I hope that helps !