Differential expression analysis using a model-based gene clustering algorithm for RNA-seq data

Differential expression analysis using a model-based gene clustering algorithm for RNA-seq data

Background: RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering is used to classify DEGs with similar expression patterns for the subsequent analyses of data from experiments such as time-courses or multi-group compa...

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Bibliographic Details
Main Authors: Kadota, K. (Author), Osabe, T. (Author), Shimizu, K. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
article
cluster analysis
Cluster Analysis
clustering algorithm
Clustering algorithms
controlled study
Differential expression
differential expression analysis
Differentially expressed gene
Expression analysis
Expression patterns
Gene clustering
Gene expression
gene expression profiling
Gene Expression Profiling
gene identification
Multi-group
Normalization algorithms
Posterior probability
probability
protein expression
RNA
RNA sequencing
RNA-seq
RNA-Seq
sequence analysis
Sequence Analysis, RNA
simulation
Time course
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