Back to Search
Start Over
Comparative analysis of differential gene expression tools for RNA sequencing time course data
- Source :
- Briefings in Bioinformatics, Briefings in Bioinformatics, 20 (1)
- Publication Year :
- 2017
- Publisher :
- Oxford University Press (OUP), 2017.
-
Abstract
- RNA sequencing (RNA-seq) has become a standard procedure to investigate transcriptional changes between conditions and is routinely used in research and clinics. While standard differential expression (DE) analysis between two conditions has been extensively studied, and improved over the past decades, RNA-seq time course (TC) DE analysis algorithms are still in their early stages. In this study, we compare, for the first time, existing TC RNA-seq tools on an extensive simulation data set and validated the best performing tools on published data. Surprisingly, TC tools were outperformed by the classical pairwise comparison approach on short time series (<br />Briefings in Bioinformatics, 20 (1)<br />ISSN:1467-5463<br />ISSN:1477-4054
- Subjects :
- Paper
Time Factors
Computer science
0206 medical engineering
RNA-Seq
02 engineering and technology
Computational biology
Signal-To-Noise Ratio
Bioinformatics
differential expression
time course RNA-seq
tools comparison
simulated and biological data sets
Massively parallel signature sequencing
03 medical and health sciences
Bayes' theorem
Robustness (computer science)
False positive paradox
Humans
Computer Simulation
Molecular Biology
030304 developmental biology
0303 health sciences
Models, Statistical
Markov chain
Sequence Analysis, RNA
Gene Expression Profiling
Computational Biology
Bayes Theorem
Molecular Sequence Annotation
Markov Chains
Data set
Pairwise comparison
Databases, Nucleic Acid
Software
020602 bioinformatics
Information Systems
Subjects
Details
- ISSN :
- 14774054 and 14675463
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- Briefings in Bioinformatics
- Accession number :
- edsair.doi.dedup.....e1a3fcfc523a855b067c71399f98e9ac