SNP Analysis

Screening the millions of reads that next-generation sequencing produces presents a major challenge when searching for candidate SNPs. Both the Maq and GSNAP algorithms include SNP screening capabilities.

Maq^[1] has a two level screening process which searches initially for differences between the reads and the reference sequence. Next a filtering step takes place which sifts the initial results looking for a minimum number of variants of the same class per column of reads, and variants embedded within high quality regions. The results are presented in a comprehensive report. You can also view your results in a Maqview or Tablet.

With GSNAP^[2] the SNP analysis takes a different approach looking at both previously reported SNPs as well as new candidates. The user must supply a list of known SNPs as well as the reads and a reference sequence. GSNAP performs a SNP-tolerant alignment of all major and minor alleles. The algorithm enables the minor alleles to be differentiated from mismatches. The results are presented in a comprehensive report. You can also view your results in Tablet.

[1] Heng Li, Jue Ruan and Richard Durbin
     Mapping short DNA sequencing reads and calling variants using mapping quality scores
     Genome Research 2008 18:1851-1858

[2] Thomas D. Wu and Serban Nacu
      Fast and SNP-tolerant detection of complex variants and splicing in short reads
      Bioinformatics 2010 26: 873-881