A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data.
Li, Xiaohong
A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data. [electronic resource] - PloS one 2017 - e0176185 p. digital
Publication Type: Comparative Study; Journal Article
1932-6203
10.1371/journal.pone.0176185 doi
Area Under Curve
Breast Neoplasms--metabolism
Computer Simulation
Datasets as Topic
Gene Expression Profiling--methods
High-Throughput Nucleotide Sequencing--methods
Humans
Microarray Analysis--methods
Models, Statistical
ROC Curve
Sequence Analysis, RNA--methods
Software
A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data. [electronic resource] - PloS one 2017 - e0176185 p. digital
Publication Type: Comparative Study; Journal Article
1932-6203
10.1371/journal.pone.0176185 doi
Area Under Curve
Breast Neoplasms--metabolism
Computer Simulation
Datasets as Topic
Gene Expression Profiling--methods
High-Throughput Nucleotide Sequencing--methods
Humans
Microarray Analysis--methods
Models, Statistical
ROC Curve
Sequence Analysis, RNA--methods
Software