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Quality control method for RNA-seq using single nucleotide polymorphism allele frequency

RNA sequencing (RNA-seq) provides information not only about the level of expression of individual genes but also about genomic sequences of host cells. When we use transcriptome data with whole-genome single nucleotide polymorphism (SNP) variant information, the allele frequency can show the geneti...

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Autor principal: Endo, Takaho A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231238/
https://www.ncbi.nlm.nih.gov/pubmed/25243705
http://dx.doi.org/10.1111/gtc.12178
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author Endo, Takaho A
author_facet Endo, Takaho A
author_sort Endo, Takaho A
collection PubMed
description RNA sequencing (RNA-seq) provides information not only about the level of expression of individual genes but also about genomic sequences of host cells. When we use transcriptome data with whole-genome single nucleotide polymorphism (SNP) variant information, the allele frequency can show the genetic composition of the cell population and/or chromosomal aberrations. Here, I show how SNPs in mRNAs can be used to evaluate RNA-seq experiments by focusing on RNA-seq data based on a recently retracted paper on stimulus-triggered acquisition of pluripotency (STAP) cells. The analysis indicated that different types of cells and chromosomal abnormalities might have been erroneously included in the dataset. This re-evaluation showed that observing allele frequencies could help in assessing the quality of samples during a study and with retrospective evaluation of experimental quality.
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spelling pubmed-42312382014-12-15 Quality control method for RNA-seq using single nucleotide polymorphism allele frequency Endo, Takaho A Genes Cells Original Articles RNA sequencing (RNA-seq) provides information not only about the level of expression of individual genes but also about genomic sequences of host cells. When we use transcriptome data with whole-genome single nucleotide polymorphism (SNP) variant information, the allele frequency can show the genetic composition of the cell population and/or chromosomal aberrations. Here, I show how SNPs in mRNAs can be used to evaluate RNA-seq experiments by focusing on RNA-seq data based on a recently retracted paper on stimulus-triggered acquisition of pluripotency (STAP) cells. The analysis indicated that different types of cells and chromosomal abnormalities might have been erroneously included in the dataset. This re-evaluation showed that observing allele frequencies could help in assessing the quality of samples during a study and with retrospective evaluation of experimental quality. BlackWell Publishing Ltd 2014-11 2014-09-21 /pmc/articles/PMC4231238/ /pubmed/25243705 http://dx.doi.org/10.1111/gtc.12178 Text en © 2014 The Authors. Genes to Cells published by Wiley Publishing Asia Pty Ltd and the Molecular Biology Society of Japan. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Endo, Takaho A
Quality control method for RNA-seq using single nucleotide polymorphism allele frequency
title Quality control method for RNA-seq using single nucleotide polymorphism allele frequency
title_full Quality control method for RNA-seq using single nucleotide polymorphism allele frequency
title_fullStr Quality control method for RNA-seq using single nucleotide polymorphism allele frequency
title_full_unstemmed Quality control method for RNA-seq using single nucleotide polymorphism allele frequency
title_short Quality control method for RNA-seq using single nucleotide polymorphism allele frequency
title_sort quality control method for rna-seq using single nucleotide polymorphism allele frequency
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231238/
https://www.ncbi.nlm.nih.gov/pubmed/25243705
http://dx.doi.org/10.1111/gtc.12178
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