PMID- 21863128
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20111110
LR  - 20240323
IS  - 1176-9351 (Electronic)
IS  - 1176-9351 (Linking)
VI  - 10
DP  - 2011
TI  - On differential gene expression using RNA-Seq data.
PG  - 205-15
LID - 10.4137/CIN.S7473 [doi]
AB  - MOTIVATION: RNA-Seq is a novel technology that provides read counts of RNA 
      fragments in each gene, including the mapped positions of each read within each 
      gene. Besides many other applications it can be used to detect differentially 
      expressed genes. Most published methods collapse the position-level read data 
      into a single gene-specific expression measurement. Statistical inference 
      proceeds by modeling these gene-level expression measurements. RESULTS: We 
      present a Bayesian method of calling differential expression (BM-DE) that 
      directly models the position-level read counts. We demonstrate the potential 
      advantage of the BM-DE method compared to existing approaches that rely on 
      gene-level aggregate data. An important additional feature of the proposed 
      approach is that BM-DE can be used to analyze RNA-Seq data from experiments 
      without biological replicates. This becomes possible since the approach works 
      with multiple position-level read counts for each gene. We demonstrate the 
      importance of modeling for position-level read counts with a yeast data set and a 
      simulation study. AVAILABILITY: A public domain R package is available from 
      http://odin.mdacc.tmc.edu/~ylji/BMDE/.
FAU - Lee, Juhee
AU  - Lee J
AD  - Department of Biostatistics, UT M.D. Anderson Cancer Center Houston, Texas, USA.
FAU - Ji, Yuan
AU  - Ji Y
FAU - Liang, Shoudan
AU  - Liang S
FAU - Cai, Guoshuai
AU  - Cai G
FAU - Muller, Peter
AU  - Muller P
LA  - eng
GR  - K25 CA123344/CA/NCI NIH HHS/United States
GR  - R01 CA132897/CA/NCI NIH HHS/United States
PT  - Journal Article
DEP - 20110801
PL  - United States
TA  - Cancer Inform
JT  - Cancer informatics
JID - 101258149
PMC - PMC3153162
OTO - NOTNLM
OT  - clustering
OT  - false discovery rate
OT  - mixture models
OT  - next-generation sequencing
EDAT- 2011/08/25 06:00
MHDA- 2011/08/25 06:01
PMCR- 2011/08/01
CRDT- 2011/08/25 06:00
PHST- 2011/08/25 06:00 [entrez]
PHST- 2011/08/25 06:00 [pubmed]
PHST- 2011/08/25 06:01 [medline]
PHST- 2011/08/01 00:00 [pmc-release]
AID - cin-10-2011-205 [pii]
AID - 10.4137/CIN.S7473 [doi]
PST - ppublish
SO  - Cancer Inform. 2011;10:205-15. doi: 10.4137/CIN.S7473. Epub 2011 Aug 1.