Literature DB >> 23559639

A tool for RNA sequencing sample identity check.

Jinyan Huang1, Jun Chen, Mark Lathrop, Liming Liang.   

Abstract

SUMMARY: RNA sequencing data are becoming a major method of choice to study transcriptomes, including the mapping of gene expression quantitative trait loci (eQTLs). RNA sample contamination or swapping is a serious problem for downstream analysis and may result in false discovery and lose power to detect the true biological relationships. When genetic data are available, for example, in eQTL studies or samples have been previously genotyped or DNA sequenced, it is possible to combine genetic data and RNA-seq data to detect sample contamination and resolve sample swapping problems. In this article, we introduce a tool (IDCheck) that allows easy assessment of concordance between genotype (from SNP arrays or DNA sequencing) and gene expression (RNA-seq) samples. IDCheck compares the identity of RNA-seq reads and SNP genotypes using a likelihood-based method. Based on maximum likelihood estimates of relevant parameters, we can detect sample contamination and identify correct sample pairs when swapping occurs. Our tool provides an efficient and convenient way to evaluate and resolve these problems. AVAILABILITY: A complete description of the software is included on the application home page. The software is freely available in the public domain at http://eqtl.rc.fas.harvard.edu/idcheck/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mesh:

Year:  2013        PMID: 23559639     DOI: 10.1093/bioinformatics/btt155

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  6 in total

1.  Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories.

Authors:  Peter A C 't Hoen; Marc R Friedländer; Jonas Almlöf; Michael Sammeth; Irina Pulyakhina; Seyed Yahya Anvar; Jeroen F J Laros; Henk P J Buermans; Olof Karlberg; Mathias Brännvall; Johan T den Dunnen; Gert-Jan B van Ommen; Ivo G Gut; Roderic Guigó; Xavier Estivill; Ann-Christine Syvänen; Emmanouil T Dermitzakis; Tuuli Lappalainen
Journal:  Nat Biotechnol       Date:  2013-09-15       Impact factor: 54.908

2.  MBV: a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets.

Authors:  Alexandre Fort; Nikolaos I Panousis; Marco Garieri; Stylianos E Antonarakis; Tuuli Lappalainen; Emmanouil T Dermitzakis; Olivier Delaneau
Journal:  Bioinformatics       Date:  2017-06-15       Impact factor: 6.937

3.  A community effort to identify and correct mislabeled samples in proteogenomic studies.

Authors:  Seungyeul Yoo; Zhiao Shi; Bo Wen; SoonJye Kho; Renke Pan; Hanying Feng; Hong Chen; Anders Carlsson; Patrik Edén; Weiping Ma; Michael Raymer; Ezekiel J Maier; Zivana Tezak; Elaine Johanson; Denise Hinton; Henry Rodriguez; Jun Zhu; Emily Boja; Pei Wang; Bing Zhang
Journal:  Patterns (N Y)       Date:  2021-05-07

4.  NGSCheckMate: software for validating sample identity in next-generation sequencing studies within and across data types.

Authors:  Sejoon Lee; Soohyun Lee; Scott Ouellette; Woong-Yang Park; Eunjung A Lee; Peter J Park
Journal:  Nucleic Acids Res       Date:  2017-06-20       Impact factor: 16.971

5.  SPEAQeasy: a scalable pipeline for expression analysis and quantification for R/bioconductor-powered RNA-seq analyses.

Authors:  Nicholas J Eagles; Emily E Burke; Jacob Leonard; Brianna K Barry; Joshua M Stolz; Louise Huuki; BaDoi N Phan; Violeta Larios Serrato; Everardo Gutiérrez-Millán; Israel Aguilar-Ordoñez; Andrew E Jaffe; Leonardo Collado-Torres
Journal:  BMC Bioinformatics       Date:  2021-05-01       Impact factor: 3.169

6.  Assessment of kinship detection using RNA-seq data.

Authors:  Natalia Blay; Eduard Casas; Iván Galván-Femenía; Jan Graffelman; Rafael de Cid; Tanya Vavouri
Journal:  Nucleic Acids Res       Date:  2019-12-02       Impact factor: 16.971

  6 in total

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