Your browser doesn't support javascript.
loading
Brief guide to RNA sequencing analysis for nonexperts in bioinformatics.
Lee, Gee-Yoon; Ham, Seokjin; Lee, Seung-Jae V.
Affiliation
  • Lee GY; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Yuseong-gu 34141, Daejeon, South Korea.
  • Ham S; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Yuseong-gu 34141, Daejeon, South Korea.
  • Lee SV; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Yuseong-gu 34141, Daejeon, South Korea. Electronic address: seungjaevlee@kaist.ac.kr.
Mol Cells ; 47(5): 100060, 2024 May.
Article in En | MEDLINE | ID: mdl-38614390
ABSTRACT
Transcriptome analysis is widely used for current biological research but remains challenging for many experimental scientists. Here, we present a brief but broad guideline for transcriptome analysis, focusing on RNA sequencing, by providing the list of publicly available datasets, tools, and R packages for practical transcriptome analysis. This work will be useful for biologists to perform key transcriptomic analysis with minimum expertise in bioinformatics.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Analysis, RNA / Computational Biology Limits: Humans Language: En Journal: Mol Cells Journal subject: BIOLOGIA MOLECULAR Year: 2024 Type: Article Affiliation country: South Korea

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Analysis, RNA / Computational Biology Limits: Humans Language: En Journal: Mol Cells Journal subject: BIOLOGIA MOLECULAR Year: 2024 Type: Article Affiliation country: South Korea