Statistical method to compare massive parallel sequencing pipelines

BMC Bioinformatics

Methodology Article

N. Leblay¹  C. Bardel¹  P. Roy¹  MH. Elsensohn¹  A. Labalme²  F. Roucher-Boulez³  A. Campan-Fournier⁴  D. Sanlaville⁴  S. Dimassi⁴  G. Lesca⁴ 

[1] Service de Biostatistique-Bioinformatique, Hospices Civils de Lyon, 162 avenue Lacassagne, F-69003, Lyon, France;Université de Lyon, Lyon, France;Université Lyon 1, Villeurbanne, France;CNRS UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique Santé, Villeurbanne, France;Service de Génétique, Hospices Civils de Lyon, Lyon, France;Université de Lyon, Lyon, France;Université Lyon 1, Villeurbanne, France;CNRS UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique Santé, Villeurbanne, France;Service de Génétique, Hospices Civils de Lyon, Lyon, France;Université de Lyon, Lyon, France;Université Lyon 1, Villeurbanne, France;Service de Génétique, Hospices Civils de Lyon, Lyon, France;Centre de Recherche en Neurosciences de Lyon, CNRS UMR 5292, INSERM U1028, Lyon, France;

关键词: Statistical methods;    Massive parallel sequencing;    Next-generation sequencing;    Pipeline comparison;    Sensitivity;    Specificity;   

DOI  :  10.1186/s12859-017-1552-9

 received in 2016-09-10, accepted in 2017-02-16,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundToday, sequencing is frequently carried out by Massive Parallel Sequencing (MPS) that cuts drastically sequencing time and expenses. Nevertheless, Sanger sequencing remains the main validation method to confirm the presence of variants. The analysis of MPS data involves the development of several bioinformatic tools, academic or commercial. We present here a statistical method to compare MPS pipelines and test it in a comparison between an academic (BWA-GATK) and a commercial pipeline (TMAP-NextGENe®), with and without reference to a gold standard (here, Sanger sequencing), on a panel of 41 genes in 43 epileptic patients. This method used the number of variants to fit log-linear models for pairwise agreements between pipelines. To assess the heterogeneity of the margins and the odds ratios of agreement, four log-linear models were used: a full model, a homogeneous-margin model, a model with single odds ratio for all patients, and a model with single intercept. Then a log-linear mixed model was fitted considering the biological variability as a random effect.ResultsAmong the 390,339 base-pairs sequenced, TMAP-NextGENe® and BWA-GATK found, on average, 2253.49 and 1857.14 variants (single nucleotide variants and indels), respectively. Against the gold standard, the pipelines had similar sensitivities (63.47% vs. 63.42%) and close but significantly different specificities (99.57% vs. 99.65%; p < 0.001). Same-trend results were obtained when only single nucleotide variants were considered (99.98% specificity and 76.81% sensitivity for both pipelines).ConclusionsThe method allows thus pipeline comparison and selection. It is generalizable to all types of MPS data and all pipelines.

【 授权许可】

CC BY   
© The Author(s). 2017

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