title: Quality control method for RNA-seq using single nucleotide polymorphism allele frequency.
abstract: 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.
authors.affiliation: RIKEN Center for Integrative Medical Science (IMS-RIKEN), 1-7-22 Suehiro-Cho, Tsurumi-Ku, Yokohama, Kanagawa, 230-0045, Japan.
authors.forename: Takaho A
authors.initials: TA
authors.lastname: Endo
mesh_terms: D000818:Animals; D002869:Chromosome Aberrations; D003198:Computer Simulation; D030541:Databases, Genetic; D005346:Fibroblast Growth Factors / Q000378:metabolism; D005787:Gene Frequency; D005838:Genotype; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D011786:Quality Control; D012333:RNA, Messenger / Q000235:genetics*; D015203:Reproducibility of Results; D017423:Sequence Analysis, RNA / Q000379:methods; D013234:Stem Cells / Q000378:metabolism
chemical_list: D012333:RNA, Messenger; D005346:Fibroblast Growth Factors