ArticleBMC genomics2012
Steps to ensure accuracy in genotype and SNP calling from Illumina sequencing data.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.
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Who cites it
73 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- GeCKO: user-friendly workflows for genotyping complex genomes using target enrichment capture. A use case on the large tetraploid durum wheat genome.Plant methods · 2024Article
- Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework.Mathematics (Basel, Switzerland) · 2023Article
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- Better safe than sorry-Whole-genome sequencing indicates that missense variants are significant in susceptibility to COVID-19.PloS one · 2023Article
- xAtlas: scalable small variant calling across heterogeneous next-generation sequencing experiments.GigaScience · 2022Article
- A pipeline for assembling low copy nuclear markers from plant genome skimming data for phylogenetic use.PeerJ · 2022Article
- A whole genome sequencing approach to anterior cruciate ligament rupture-a twin study in two unrelated families.PloS one · 2022Article
- Comparison of seven SNP calling pipelines for the next-generation sequencing data of chickens.PloS one · 2022Article
- Biased allelic expression in tissues of F1 hybrids between tropical and temperate lotus (Nelumbo nuicfera).Plant molecular biology · 2021Article
- Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels.BMC bioinformatics · 2021Article
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- Genome-wide Identification and Analysis of Splicing QTLs in Multiple Sclerosis by RNA-Seq Data.Frontiers in genetics · 2021Article
13 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
backgroundAccurate calling of SNPs and genotypes from next-generation sequencing data is an essential prerequisite for most human genetics studies. A number of computational steps are required or recommended when translating the raw sequencing data into the final calls. However, whether each step does contribute to the performance of variant calling and how it affects the accuracy still remain unclear, making it difficult to select and arrange appropriate steps to derive high quality variants from different sequencing data. In this study, we made a systematic assessment of the relative contribution of each step to the accuracy of variant calling from Illumina DNA sequencing data.
resultsWe found that the read preprocessing step did not improve the accuracy of variant calling, contrary to the general expectation. Although trimming off low-quality tails helped align more reads, it introduced lots of false positives. The ability of markup duplication, local realignment and recalibration, to help eliminate false positive variants depended on the sequencing depth. Rearranging these steps did not affect the results. The relative performance of three popular multi-sample SNP callers, SAMtools, GATK, and GlfMultiples, also varied with the sequencing depth.
conclusionsOur findings clarify the necessity and effectiveness of computational steps for improving the accuracy of SNP and genotype calls from Illumina sequencing data and can serve as a general guideline for choosing SNP calling strategies for data with different coverage.
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