Hi,
I recently used several aligners to do the tests for SNPs calling. Without any iteration step, the bowtie2-local-very sensitive performed better than bwa. It could call more real SNPs than both bwa and smalt. But after the iteration steps, bowtie2 only yielded a few SNPs and lost many real ones. With the same default recalibration parameters, SNPs based on bwa alignment were very constant after 5 iterations.
Can you guys help me to figure it out? How can I keep more SNPs based on bowtie2 alignment after iterations?
Thanks in advance!
Wei
I recently used several aligners to do the tests for SNPs calling. Without any iteration step, the bowtie2-local-very sensitive performed better than bwa. It could call more real SNPs than both bwa and smalt. But after the iteration steps, bowtie2 only yielded a few SNPs and lost many real ones. With the same default recalibration parameters, SNPs based on bwa alignment were very constant after 5 iterations.
Can you guys help me to figure it out? How can I keep more SNPs based on bowtie2 alignment after iterations?
Thanks in advance!
Wei