Unknown

Dataset Information

0

PICNIC: an algorithm to predict absolute allelic copy number variation with microarray cancer data.

ABSTRACT: High-throughput oligonucleotide microarrays are commonly employed to investigate genetic disease, including cancer. The algorithms employed to extract genotypes and copy number variation function optimally for diploid genomes usually associated with inherited disease. However, cancer genomes are aneuploid in nature leading to systematic errors when using these techniques. We introduce a preprocessing transformation and hidden Markov model algorithm bespoke to cancer. This produces genotype classification, specification of regions of loss of heterozygosity, and absolute allelic copy number segmentation. Accurate prediction is demonstrated with a combination of independent experimental techniques. These methods are exemplified with affymetrix genome-wide SNP6.0 data from 755 cancer cell lines, enabling inference upon a number of features of biological interest. These data and the coded algorithm are freely available for download.

SUBMITTER: Greenman CD 

PROVIDER: S-EPMC2800165 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

Json Xml
altmetric image

Publications

PICNIC: an algorithm to predict absolute allelic copy number variation with microarray cancer data.

Greenman Chris D CD   Bignell Graham G   Butler Adam A   Edkins Sarah S   Hinton Jon J   Beare Dave D   Swamy Sajani S   Santarius Thomas T   Chen Lina L   Widaa Sara S   Futreal P Andy PA   Stratton Michael R MR  

Biostatistics (Oxford, England) 20091015 1

High-throughput oligonucleotide microarrays are commonly employed to investigate genetic disease, including cancer. The algorithms employed to extract genotypes and copy number variation function optimally for diploid genomes usually associated with inherited disease. However, cancer genomes are aneuploid in nature leading to systematic errors when using these techniques. We introduce a preprocessing transformation and hidden Markov model algorithm bespoke to cancer. This produces genotype class  ...[more]

Similar Datasets

Unknown wuHMM: a robust algorithm to detect DNA copy number variation using long oligonucleotide microarray data.
| S-EPMC2367727 | biostudies-literature
Genomics wuHMM: a robust algorithm to detect DNA copy number variation using long oligonucleotide microarray data
2008-03-12 | GSE10511 | GEO
Transcriptomics wuHMM: a robust algorithm to detect DNA copy number variation using long oligonucleotide microarray data
2008-03-11 | E-GEOD-10511 | biostudies-arrayexpress
Unknown Copy number variation signature to predict human ancestry.
| S-EPMC3598683 | biostudies-literature
Unknown Measurement of absolute copy number variation reveals association with essential hypertension.
| S-EPMC4107748 | biostudies-literature
Unknown Absolute copy number fitting from shallow whole genome sequencing data
| S-BSST685 | biostudies-other
Unknown Modified screening and ranking algorithm for copy number variation detection.
| S-EPMC4410664 | biostudies-literature
Unknown Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data.
| S-EPMC2148068 | biostudies-literature
Unknown EnsembleCNV: an ensemble machine learning algorithm to identify and genotype copy number variation using SNP array data.
| S-EPMC6468244 | biostudies-literature
Genomics Gene copy number variation profiling by microarray
| PRJNA712994 | ENA