Mapping short DNA sequencing reads and calling variants using mapping quality scores.

By Heng Li, Jue Ruan, Richard Durbin. Genome Research, 2008

1,205 citations recorded by the source corpus.

New sequencing technologies promise a new era in the use of DNA sequence. However, some of these technologies produce very short reads, typically of a few tens of base pairs, and to use these reads effectively requires new algorithms and software. In particular, there is a major issue in efficiently aligning short reads to a reference genome and handling ambiguity or lack of accuracy in this alignment. Here we introduce the concept of mapping quality, a measure of the confidence that a read actually comes from the position it is aligned to by the mapping algorithm. We describe the software MAQ that can build assemblies by mapping shotgun short reads to a reference genome, using quality scores to derive genotype calls of the consensus sequence of a diploid genome, e.g., from a human sample. MAQ makes full use of mate-pair information and estimates the error probability of each read alignment. Error probabilities are also derived for the final genotype calls, using a Bayesian statistical model that incorporates the mapping qualities, error probabilities from the raw sequence quality scores, sampling of the two haplotypes, and an empirical model for correlated errors at a site. Both read mapping and genotype calling are evaluated on simulated data and real data. MAQ is accurate, efficient, versatile, and user-friendly. It is freely available at http://maq.sourceforge.net.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d1999697b7629d9f19e88b284504ff7222297c59

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Citations in the corpus

Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease (2011, methodology): “Reads of 76 bp, 36 bp and 52 bp were aligned to the genome using MAQ algorith”
BSMAP: whole genome bisulfite sequence MAPping program (2009, neutral): “Because of these advantages, the seeding algorithm has been incorporated into most short read mapping software, including SOAP [5], ELAND, MAQ [6], and RMAP [7].”
Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications (2014, background): “The most common approach is to map reads to a reference genome 6,10–13 and either scan for systematic differences with the reference or identify haplotypes that are well supported by the data 14 .”
Frequent mutations of chromatin remodeling genes in transitional cell carcinoma of the bladder (2011, background): “) and aligned them to the reference human genome (hg18) using MA”
The Next-Generation Sequencing Revolution and Its Impact on Genomics (2013, neutral): “…variantcalling algorithms have been developed for the detection and genotyping of germline SNPs (DePristo et al., 2011; Koboldt et al., 2009; Li et al., 2008; McKenna et al., 2010; Shen et al., 2010) and small indels (Emde et al., 2012; Leone et al., 2013; Ye et al., 2009) in…”
BFAST: An Alignment Tool for Large Scale Genome Resequencing (2009, methodology): “This is typically performed by passing it through an index of the reference genome [8–14], or by indexing the reads and searching the reference genome [15,16].”
Next-generation sequencing platforms. (2013, background): “Specific algorithms to approach short read alignment have been devised; they provide a score-based metric indicative of that sequence’s best fit in the genome, whereby sequences that contain mostly or entirely repetitive content score lowest due to the uncertainty of their origin (22, 23).”
Massive Genomic Rearrangement Acquired in a Single Catastrophic Event during Cancer Development (2011, methodology): “Reads were aligned to the reference human genome (NCBI build 36) using MAQ (Li et al., 2008).”
A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries (2011, methodology): “After sequencing and mapping of data to the genome, the genotypes of these 24 loci are determined using a simple quality-aware Bayesian genotyping algorithm similar to published tools [29,30] and compared to those previously ascertained using a genotyping technology such as the Sequenom HME platform”
Computational pan-genomics: status, promises and challenges (2016, background): “practice include read mapping qualities [155] and genotype likelihoods [156].”
MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping (2013, methodology): “The hash-based aligners, Eland (AJ Cox, Illumina, San Diego), MAQ (Li et al. 2008), mrFAST/mrsFast (Alkan et al. 2009; Hach et al. 2010), SHRiMP (Rumble et al. 2009; David et al. t2011), and ZOOM (Lin et al. 2008; Zhang et al. 2010) hash the reads and fit these hashes to the reference genome, while ”
TopHat: discovering splice junctions with RNA-Seq (2009, neutral): “Availability: TopHat is free, open-source software available from http://tophat.cbcb.umd.edu Contact: cole@cs.umd.edu Supplementary information: Supplementary data are available at Bioinformatics online.”