DocumentCode
3454000
Title
Identifying differential expression for RNA-seq data with no replication
Author
Jungsoo Gim ; Taesung Park
Author_Institution
Interdiscipl. Program for Bioinf., Seoul Nat. Univ., Seoul, South Korea
fYear
2012
fDate
4-7 Oct. 2012
Firstpage
847
Lastpage
851
Abstract
Transcriptional process is a starting point of biological function. In particular, transcriptomes that display differential expression in different conditions are likely to be key elements in understanding mechanisms causing those differences. A number of statistical approaches have been suggested for discovery of differential expression in microarray platform with replicated samples. However, many of sequencing-based studies tend to have very small or even no replicated sample due to high cost. Because accurate variance estimation is not straightforward with no replicated sample, accurate testing of differential expression is not easy. Here, we propose the permutation-based local pooled error (pLPE) method. By permuting local genes, pLPE method estimates variance more reliably and, thus, facilitates a differential expression analysis with no replicated sample.
Keywords
RNA; genetics; molecular biophysics; molecular configurations; statistical analysis; RNA-seq data; accurate testing; biological function; differential expression analysis; microarray platform; pLPE method; permutation-based local pooled error method; permuting local genes; replicated samples; statistical approaches; transcriptional process; variance estimation; Bioinformatics; Biological system modeling; Data models; Liver; Reliability; Testing; DEG; LPE; RNA-seq; no replicates;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on
Conference_Location
Philadelphia, PA
Print_ISBN
978-1-4673-2746-6
Electronic_ISBN
978-1-4673-2744-2
Type
conf
DOI
10.1109/BIBMW.2012.6470252
Filename
6470252
Link To Document