Literature DB >> 25577376

Quality control of RNA-seq experiments.

Xing Li1, Asha Nair, Shengqin Wang, Liguo Wang.   

Abstract

Direct sequencing of the complementary DNA (cDNA) using high-throughput sequencing technologies (RNA-seq) is widely used and allows for more comprehensive understanding of the transcriptome than microarray. In theory, RNA-seq should be able to precisely identify and quantify all RNA species, small or large, at low or high abundance. However, RNA-seq is a complicated, multistep process involving reverse transcription, amplification, fragmentation, purification, adaptor ligation, and sequencing. Improper operations at any of these steps could make biased or even unusable data. Additionally, RNA-seq intrinsic biases (such as GC bias and nucleotide composition bias) and transcriptome complexity can also make data imperfect. Therefore, comprehensive quality assessment is the first and most critical step for all downstream analyses and results interpretation. This chapter discusses the most widely used quality control metrics including sequence quality, sequencing depth, reads duplication rates (clonal reads), alignment quality, nucleotide composition bias, PCR bias, GC bias, rRNA and mitochondria contamination, coverage uniformity, etc.

Mesh:

Substances:

Year:  2015        PMID: 25577376     DOI: 10.1007/978-1-4939-2291-8_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  21 in total

Review 1.  A simple guide to de novo transcriptome assembly and annotation.

Authors:  Venket Raghavan; Louis Kraft; Fantin Mesny; Linda Rigerte
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

Review 2.  The Architecture of a Precision Oncology Platform.

Authors:  Alessandro Laganà
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

3.  The Expression and Bioinformatics Analysis of Circular RNAs in Endometritis Mouse Uterus Tissues.

Authors:  Zhiqiang Li; Liying Shi; Qianqing Li; Jing Zhao; Wenfa Lu; Jun Wang
Journal:  Molecules       Date:  2022-06-08       Impact factor: 4.927

4.  Sequencing, De novo Assembly, Functional Annotation and Analysis of Phyllanthus amarus Leaf Transcriptome Using the Illumina Platform.

Authors:  Aparupa Bose Mazumdar; Sharmila Chattopadhyay
Journal:  Front Plant Sci       Date:  2016-01-28       Impact factor: 5.753

5.  dupRadar: a Bioconductor package for the assessment of PCR artifacts in RNA-Seq data.

Authors:  Sergi Sayols; Denise Scherzinger; Holger Klein
Journal:  BMC Bioinformatics       Date:  2016-10-21       Impact factor: 3.169

6.  Maintaining RNA Integrity for Transcriptomic Profiling of Ex Vivo Cultured Limbal Epithelial Stem Cells after Fluorescence-Activated Cell Sorting (FACS).

Authors:  Lei Liu; Frederik Mølgaard Nielsen; Simone Elkjær Riis; Jeppe Emmersen; Trine Fink; Jesper Østergaard Hjortdal; Chris Bath; Vladimir Zachar
Journal:  Biol Proced Online       Date:  2017-12-12       Impact factor: 3.244

Review 7.  Screening the Molecular Framework Underlying Local Dendritic mRNA Translation.

Authors:  Sanjeev V Namjoshi; Kimberly F Raab-Graham
Journal:  Front Mol Neurosci       Date:  2017-02-24       Impact factor: 5.639

8.  Soil Microbial Indicators within Rotations and Tillage Systems.

Authors:  Gevan D Behnke; Nakian Kim; Maria C Zabaloy; Chance W Riggins; Sandra Rodriguez-Zas; Maria B Villamil
Journal:  Microorganisms       Date:  2021-06-08

9.  Whole blood defensin mRNA expression is a predictive biomarker of docetaxel response in castration-resistant prostate cancer.

Authors:  Manish Kohli; Charles Yf Young; Donald J Tindall; Debashis Nandy; Kyle M McKenzie; Graham H Bevan; Krishna Vanaja Donkena
Journal:  Onco Targets Ther       Date:  2015-07-30       Impact factor: 4.147

10.  RNA Quality Control Using External Standard RNA.

Authors:  Takema Hasegawa; Junko Takahashi; Hitoshi Iwahashi
Journal:  Pol J Microbiol       Date:  2018
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.