An all-statistics, high-speed algorithm for the analysis of copy number variation in genomes

NCUIR > college of Health Sciences and Technology > Institute of Systems Biology and Bioinformatics > journal & Dissertation > Item 987654321/51082

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51082

Title:	An all-statistics, high-speed algorithm for the analysis of copy number variation in genomes
Authors:	Chen,CH;Lee,HC;Ling,Q;Chen,HR;Ko,YA;Tsou,TS;Wang,SC;Wu,LC;Lee,HC
Contributors:	系統生物與生物資訊研究所
Keywords:	ARRAY-CGH DATA;CIRCULAR BINARY SEGMENTATION;OLIGONUCLEOTIDE MICROARRAY;HYBRIDIZATION DATA;ACCURATE
Date:	2011
Issue Date:	2012-03-27 18:20:53 (UTC+8)
Publisher:	國立中央大學
Abstract:	Detection of copy number variation (CNV) in DNA has recently become an important method for understanding the pathogenesis of cancer. While existing algorithms for extracting CNV from microarray data have worked reasonably well, the trend towards ever larger sample sizes and higher resolution microarrays has vastly increased the challenges they face. Here, we present Segmentation analysis of DNA (SAD), a clustering algorithm constructed with a strategy in which all operational decisions are based on simple and rigorous applications of statistical principles, measurement theory and precise mathematical relations. Compared with existing packages, SAD is simpler in formulation, more user friendly, much faster and less thirsty for memory, offers higher accuracy and supplies quantitative statistics for its predictions. Unique among such algorithms, SAD's running time scales linearly with array size; on a typical modern notebook, it completes high-quality CNV analyses for a 250 thousand-probe array in similar to 1 s and a 1.8 million-probe array in similar to 8 s.
Relation:	NUCLEIC ACIDS RESEARCH
Appears in Collections:	[Institute of Systems Biology and Bioinformatics] journal & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	733	View/Open

社群 sharing

Loading...