Evaluation of methods for differential expression analysis on multi-group RNA-seq count data.
about
Empirical assessment of analysis workflows for differential expression analysis of human samples using RNA-SeqEvaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.In Papyro Comparison of TMM (edgeR), RLE (DESeq2), and MRN Normalization Methods for a Simple Two-Conditions-Without-Replicates RNA-Seq Experimental Design.Metastatic ability and the epithelial-mesenchymal transition in induced cancer stem-like hepatoma cells.Silhouette Scores for Arbitrary Defined Groups in Gene Expression Data and Insights into Differential Expression Results.Biomarker Identification from RNA-Seq Data using a Robust Statistical Approach.
P2860
Evaluation of methods for differential expression analysis on multi-group RNA-seq count data.
description
2015 nî lūn-bûn
@nan
2015 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2015 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
name
Evaluation of methods for diff ...... ulti-group RNA-seq count data.
@ast
Evaluation of methods for diff ...... ulti-group RNA-seq count data.
@en
type
label
Evaluation of methods for diff ...... ulti-group RNA-seq count data.
@ast
Evaluation of methods for diff ...... ulti-group RNA-seq count data.
@en
prefLabel
Evaluation of methods for diff ...... ulti-group RNA-seq count data.
@ast
Evaluation of methods for diff ...... ulti-group RNA-seq count data.
@en
P2860
P50
P1433
P1476
Evaluation of methods for diff ...... ulti-group RNA-seq count data.
@en
P2093
Kentaro Shimizu
P2860
P2888
P356
10.1186/S12859-015-0794-7
P577
2015-11-04T00:00:00Z
P5875
P6179
1038311518