Hi! Thanks for your prompt reply! I wondered about using bwa or bowtie, but using them wouldn' t imply losing new variants? I could just quantify the number of sequences matching those I have as references. Is it right?
Hello!
I'm approaching a dna mutation analysis for the first time. I have DNA sequences of a structural gene (454 reads, about 450 bp, single end) sequenced in 10 samples and I need to find mutations and quantify the abundance of each mutant in each sample.
This is how I'm thinking to proceed:
- demultiplexing sequences using qiime
- trimming low quality bases and filtering reads too short
- clustering them at 100% similarity using usearch
- aligning centroids to some sequences found at NCBI using mummer
My questions are:
First of all, is my approach correct? Does anybody have experience in this kind of analysis and which approach is used?
Then, I don't know if mummer is the good choice... It is designed for snp discover in genomes, so I don't know if it could be a good idea using it for sequences that I expect to be very similar among them. If not, any other suggestion about software to use?
Thanks
Francesca
1 answer
I'd skip clustering and just align everything. Just use a few more cores. I'd give BWA a try rather than mummer, mostly because BWA typically produces good quality results in downstream variant calling and also because it's reasonably fast.
BWA is probably the most popular aligner used to find new variants, so no it won't lose them (unless the sequence is very highly divergent).
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