PMID- 22689750
OWN - NLM
STAT- MEDLINE
DCOM- 20130131
LR  - 20211021
IS  - 1367-4811 (Electronic)
IS  - 1367-4803 (Print)
IS  - 1367-4803 (Linking)
VI  - 28
IP  - 12
DP  - 2012 Jun 15
TI  - Statistical model-based testing to evaluate the recurrence of genomic 
      aberrations.
PG  - i115-20
LID - 10.1093/bioinformatics/bts203 [doi]
AB  - MOTIVATION: In cancer genomes, chromosomal regions harboring cancer genes are 
      often subjected to genomic aberrations like copy number alteration and loss of 
      heterozygosity. Given this, finding recurrent genomic aberrations is considered 
      an apt approach for screening cancer genes. Although several permutation-based 
      tests have been proposed for this purpose, none of them are designed to find 
      recurrent aberrations from the genomic dataset without paired normal sample 
      controls. Their application to unpaired genomic data may lead to false 
      discoveries, because they retrieve pseudo-aberrations that exist in normal 
      genomes as polymorphisms. RESULTS: We develop a new parametric method named 
      parametric aberration recurrence test (PART) to test for the recurrence of 
      genomic aberrations. The introduction of Poisson-binomial statistics allow us to 
      compute small P-values more efficiently and precisely than the previously 
      proposed permutation-based approach. Moreover, we extended PART to cover unpaired 
      data (PART-up) so that there is a statistical basis for analyzing unpaired 
      genomic data. PART-up uses information from unpaired normal sample controls to 
      remove pseudo-aberrations in unpaired genomic data. Using PART-up, we 
      successfully predict recurrent genomic aberrations in cancer cell line samples 
      whose paired normal sample controls are unavailable. This article thus proposes a 
      powerful statistical framework for the identification of driver aberrations, 
      which would be applicable to ever-increasing amounts of cancer genomic data seen 
      in the era of next generation sequencing. AVAILABILITY: Our implementations of 
      PART and PART-up are available from http://www.hgc.jp/~niiyan/PART/manual.html.
FAU - Niida, Atushi
AU  - Niida A
AD  - Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 
      Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. aniida@ims.u-tokyo.ac.jp
FAU - Imoto, Seiya
AU  - Imoto S
FAU - Shimamura, Teppei
AU  - Shimamura T
FAU - Miyano, Satoru
AU  - Miyano S
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - England
TA  - Bioinformatics
JT  - Bioinformatics (Oxford, England)
JID - 9808944
SB  - IM
MH  - Cell Line, Tumor
MH  - *Chromosome Aberrations
MH  - Genes, Neoplasm
MH  - Genomics/*methods
MH  - Humans
MH  - *Models, Statistical
MH  - Neoplasms/*genetics
MH  - Recurrence
PMC - PMC3371835
EDAT- 2012/06/13 06:00
MHDA- 2013/02/01 06:00
PMCR- 2012/06/09
CRDT- 2012/06/13 06:00
PHST- 2012/06/13 06:00 [entrez]
PHST- 2012/06/13 06:00 [pubmed]
PHST- 2013/02/01 06:00 [medline]
PHST- 2012/06/09 00:00 [pmc-release]
AID - bts203 [pii]
AID - 10.1093/bioinformatics/bts203 [doi]
PST - ppublish
SO  - Bioinformatics. 2012 Jun 15;28(12):i115-20. doi: 10.1093/bioinformatics/bts203.