PyroHMMsnp: an SNP caller for Ion Torrent and 454 sequencing data

Abstract

Both 454 and Ion Torrent sequencers are capable of producing large amounts of long high-quality sequencing reads. However, as both methods sequence homopolymers in one cycle, they both suffer from homopolymer uncertainty and incorporation asynchronization. In mapping, such sequencing errors could shift alignments around homopolymers and thus induce incorrect mismatches, which have become a critical barrier against the accurate detection of single nucleotide polymorphisms (SNPs). In this article, we propose a hidden Markov model (HMM) to statistically and explicitly formulate homopolymer sequencing errors by the overcall, undercall, insertion and deletion. We use a hierarchical model to describe the sequencing and base-calling processes, and we estimate parameters of the HMM from resequencing data by an expectation-maximization algorithm. Based on the HMM, we develop a realignment-based SNP-calling program, termed PyroHMMsnp, which realigns read sequences around homopolymers according to the error model and then infers the underlying genotype by using a Bayesian approach. Simulation experiments show that the performance of PyroHMMsnp is exceptional across various sequencing coverages in terms of sensitivity, specificity and F1 measure, compared with other tools. Analysis of the human resequencing data shows that PyroHMMsnp predicts 12.9% more SNPs than Samtools while achieving a higher specificity. (http://code.google.com/p/pyrohmmsnp/).

Comparison of Metatranscriptomic Samples Based on k-Tuple Frequencies

“…According to sequencing error features of the 454 platform [37]–[39], we added 1% indel errors and 0.1% substitution errors to the original sequencing data. The simulated reads set with the preset error rates are generated with a pyrosequencing 454 simulator, FlowSim [37].…”

Single Nucleotide Polymorphisms (SNPs)

“…A hidden Markov model (HMM) was proposed to statistically and explicitly formulate these sequencing errors called PyroHMMsnp. PyroHMMsnp is an SNP-calling program that realigns the read sequences according to the error model and infers the underlying genotype by a Bayesian approach [ 112 ]. The current state-of-the-art 454 platform marketed by Roche Applied Science with the GS FLX Titanium system is capable of generating 700 megabase (Mb) of sequence in 700 bp reads in a 23 h run with an accuracy of 99.9 % after fi lter.…”

Efficiency of Corynebacterium pseudotuberculosis Cp31 Genome Assembly with the Hi-Q Enzyme on an Ion Torrent PGM Sequencing Platform

“…These are synthesis-based methods that measure reagent flow because the intensity of the flow of reactants is directly proportional to the amount of nucleotides incorporated. However, the relationship between the measured flow intensity and the number of nucleotides incorporated is nonlinear in homopolymeric regions, causing frequent errors in determining the length of such regions, which results in insertions and deletions [8].…”