<p>Hello,</p>

<p>Thank you for the previous answers to my questions here (https://www.biostars.org/p/135443/#136088). I have a couple of follow up questions.</p>

<p>Once SNPs are discovered, predictions are listed in the fasta files, and they are typically 60bp, with the SNP located in the middle of the prediction. This is true whether I use 100bp reads or 50bp reads. Now, coherence is established by splitting the 60bp prediction into k-mers (k=31) and assesing their k-mer coverage by all samples allowing one mismatch. And if at least one sample has a k-coverage less than 4, the SNP is considered uncoherent.</p>

<p>I was wondering if the length of the prediction can have an effect on coherency? Should I try to lower the k-mer size for shorter reads?</p>

<p>I was also wondering what is the effect of various coverage in different samples? Should we aim to subsample to the same coverage level?</p>

<p>Lastly, I tried genotype discovery with a -P of 6, are the genotypes the ones reported in the fasta file? In some regions I expect more than 2 genotypes.</p>

<p>Thank you,</p>

<p>Adrian</p>

Hi Adrian.

Without options `-t` or `-T` the length of the prediction is 2k-1 (should be 61 with k=31). With bigger *k*, the prediction is bigger. However, each prediction (without contigs/unitigs extensions) contains exactly *k* k-mers. Thus the number of tested positions for the coherency remains the same with big or small k-mers. By the way, longer kmers may be more difficult to exist in the reads.

I invite you to read the NAR paper in which the effect of kmer lengh is analysed on a set of human reads.

Currently the coverage threshold is applied per read set. However it is not possible yet to fix a coverage per read set. This improvement is necessary and we are currently working on this feature. If your coverages are high and highly dissimilar, it may be a good idea to subsample larger read sets.

Your last question is a bit more tricky. The `-P` behavior depends on the complexity of the combinations of SNPs. Clearly with `-b 0` or `-b 1`, SNPs ---A----C---- + ---A----G---- + ---T----C---- + ---T----G---- for instance are not detected. In this case, with `-b 2` variants are independently detected: (-A----C---/-A----G---), (-T----C---/-T----G---), (---A----C-,---T----C-), and (---A----G-,---T----G-) are detected --> the 2 first detect the C/G SNP with the two possible contexts (A and T) and the two last detects the variant A/T either with context C or G.

Another possibility is ---A----C---- + ---A----G---- + ---T----C---- (without ---A----G-,---T----G-). In this case b 0 detects nothing, while b 1 or b2 detect (-A----C---/-A----G---), and (---A----C-,---T----C-).

I hope this helps.

Best, Pierre