Bias in RNA-seq Library Preparation: Current Challenges and Solutions. (20th April 2021)

• Record Type: Journal Article
• Authors: Shi, Huajuan; Zhou, Ying; Jia, Erteng; Pan, Min; Bai, Yunfei; Ge, Qinyu
• Other Names: Raju Nagarajan Academic Editor.
• Is Part Of: BioMed research international. Volume 2021(2021)
• Publication Date: 2021-04-20
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2021/6647597
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Although RNA sequencing (RNA-seq) has become the most advanced technology for transcriptome analysis, it also confronts various challenges. As we all know, the workflow of RNA-seq is extremely complicated and it is easy to produce bias. This may damage the quality of RNA-seq dataset and lead to an incorrect interpretation for sequencing result. Thus, our detailed understanding of the source and nature of these biases is essential for the interpretation of RNA-seq data, finding methods to improve the quality of RNA-seq experimental, or development bioinformatics tools to compensate for these biases. Here, we discuss the sources of experimental bias in RNA-seq. And for each type of bias, we discussed the method for improvement, in order to provide some useful suggestions for researcher in RNA-seq experimental.