title: Measure transcript integrity using RNA-seq data.
abstract: BACKGROUND
  Stored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substantially degraded. RNA degradation distorts the RNA-seq read coverage in a gene-specific manner, and has profound influences on whole-genome gene expression profiling.
  
  
  RESULTS
  We developed the transcript integrity number (TIN) to measure RNA degradation. When applied to 3 independent RNA-seq datasets, we demonstrated TIN is a reliable and sensitive measure of the RNA degradation at both transcript and sample level. Through comparing 10 prostate cancer clinical samples with lower RNA integrity to 10 samples with higher RNA quality, we demonstrated that calibrating gene expression counts with TIN scores could effectively neutralize RNA degradation effects by reducing false positives and recovering biologically meaningful pathways. When further evaluating the performance of TIN correction using spike-in transcripts in RNA-seq data generated from the Sequencing Quality Control consortium, we found TIN adjustment had better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91, accuracy = 0.90), as compared to gene expression analysis results without TIN correction (sensitivity = 0.98, specificity = 0.50, accuracy = 0.86).
  
  
  CONCLUSIONS
  TIN is a reliable measurement of RNA integrity and a valuable approach used to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. wang.liguo@mayo.edu.
authors: Liguo
authors: L
authors: Wang
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. nie.jinfujeff@mayo.edu.
authors: Jinfu
authors: J
authors: Nie
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. Sicotte.Hugues@mayo.edu.
authors: Hugues
authors: H
authors: Sicotte
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. Li.Ying@mayo.edu.
authors: Ying
authors: Y
authors: Li
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. eckelpassow.jeanette@mayo.edu.
authors: Jeanette E
authors: JE
authors: Eckel-Passow
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. Dasari.Surendra@mayo.edu.
authors: Surendra
authors: S
authors: Dasari
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. Vedell.Peter@mayo.edu.
authors: Peter T
authors: PT
authors: Vedell
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. Barman.Poulami@mayo.edu.
authors: Poulami
authors: P
authors: Barman
authors: Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, 55905, USA. Wang.Liewei@mayo.edu.
authors: Liewei
authors: L
authors: Wang
authors: Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, 55905, USA. Weinshilboum.Richard@mayo.edu.
authors: Richard
authors: R
authors: Weinshiboum
authors: Department of laboratory medicine and pathology, Mayo Clinic, Rochester, MN, 55905, USA. Jen.Jin@mayo.edu.
authors: Jin
authors: J
authors: Jen
authors: Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, 55905, USA. Huang.Haojie@mayo.edu.
authors: Haojie
authors: H
authors: Huang
authors: Department of Oncology, Mayo Clinic, Rochester, MN, 55905, USA. kohli.manish@mayo.edu.
authors: Manish
authors: M
authors: Kohli
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. kocher.jeanpierre@mayo.edu.
authors: Jean-Pierre A
authors: JP
authors: Kocher
mesh_terms: D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing / Q000592:standards*; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000235:genetics*; D011786:Quality Control; D020871:RNA Stability / Q000235:genetics*; D012333:RNA, Messenger / Q000737:chemistry / Q000235:genetics*; D012334:RNA, Neoplasm / Q000737:chemistry / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000592:standards*
chemical_list: D012333:RNA, Messenger; D012334:RNA, Neoplasm