Dataset Information

SWEEP: A Tool for Filtering High-Quality SNPs in Polyploid Crops.

ABSTRACT: High-throughput next-generation sequence-based genotyping and single nucleotide polymorphism (SNP) detection opens the door for emerging genomics-based breeding strategies such as genome-wide association analysis and genomic selection. In polyploids, SNP detection is confounded by a highly similar homeologous sequence where a polymorphism between subgenomes must be differentiated from a SNP. We have developed and implemented a novel tool called SWEEP: Sliding Window Extraction of Explicit Polymorphisms. SWEEP uses subgenome polymorphism haplotypes as contrast to identify true SNPs between genotypes. The tool is a single command script that calls a series of modules based on user-defined options and takes sorted/indexed bam files or vcf files as input. Filtering options are highly flexible and include filtering based on sequence depth, alternate allele ratio, and SNP quality on top of the SWEEP filtering procedure. Using real and simulated data we show that SWEEP outperforms current SNP filtering methods for polyploids. SWEEP can be used for high-quality SNP discovery in polyploid crops.

SUBMITTER: Clevenger JP

PROVIDER: S-EPMC4555216 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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SWEEP: A Tool for Filtering High-Quality SNPs in Polyploid Crops.

Clevenger Josh P JP Ozias-Akins Peggy P

G3 (Bethesda, Md.) 20150706 9

High-throughput next-generation sequence-based genotyping and single nucleotide polymorphism (SNP) detection opens the door for emerging genomics-based breeding strategies such as genome-wide association analysis and genomic selection. In polyploids, SNP detection is confounded by a highly similar homeologous sequence where a polymorphism between subgenomes must be differentiated from a SNP. We have developed and implemented a novel tool called SWEEP: Sliding Window Extraction of Explicit Polymo ...[more]

PMID: 26153076

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Project description:Article summaries' information and structure may influence researchers/clinicians' decisions to conduct deeper full-text analyses. Specifically, abstracts of systematic reviews (SRs) and meta-analyses (MA) should provide structured summaries for quick assessment. This study explored a method for determining the methodological quality and bias risk of full-text reviews using abstract information alone.Systematic literature searches for SRs and/or MA about psoriasis were undertaken on MEDLINE, EMBASE, and Cochrane database. For each review, quality, abstract-reporting completeness, full-text methodological quality, and bias risk were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-analyses for abstracts (PRISMA-A), Assessing the Methodological Quality of Systematic Reviews (AMSTAR), and ROBIS tools, respectively. Article-, author-, and journal-derived metadata were systematically extracted from eligible studies using a piloted template, and explanatory variables concerning abstract-reporting quality were assessed using univariate and multivariate-regression models. Two classification models concerning SRs' methodological quality and bias risk were developed based on per-item and total PRISMA-A scores and decision-tree algorithms. This work was supported, in part, by project ICI1400136 (JR). No funding was received from any pharmaceutical company.This study analysed 139 SRs on psoriasis interventions. On average, they featured 56.7% of PRISMA-A items. The mean total PRISMA-A score was significantly higher for high-methodological-quality SRs than for moderate- and low-methodological-quality reviews. SRs with low-bias risk showed higher total PRISMA-A values than reviews with high-bias risk. In the final model, only 'authors per review >?6' (OR: 1.098; 95%CI: 1.012-1.194), 'academic source of funding' (OR: 3.630; 95%CI: 1.788-7.542), and 'PRISMA-endorsed journal' (OR: 4.370; 95%CI: 1.785-10.98) predicted PRISMA-A variability. Reviews with a total PRISMA-A score <?6, lacking identification as SR or MA in the title, and lacking explanation concerning bias risk assessment methods were classified as low-methodological quality. Abstracts with a total PRISMA-A score ? 9, including main outcomes results and explanation bias risk assessment method were classified as having low-bias risk.The methodological quality and bias risk of SRs may be determined by abstract's quality and completeness analyses. Our proposal aimed to facilitate synthesis of evidence evaluation by clinical professionals lacking methodological skills. External validation is necessary.

Dataset Information

SWEEP: A Tool for Filtering High-Quality SNPs in Polyploid Crops.

Publications

SWEEP: A Tool for Filtering High-Quality SNPs in Polyploid Crops.

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