Cargando…

A new analysis tool for individual-level allele frequency for genomic studies

BACKGROUND: Allele frequency is one of the most important population indices and has been broadly applied to genetic/genomic studies. Estimation of allele frequency using genotypes is convenient but may lose data information and be sensitive to genotyping errors. RESULTS: This study utilizes a unifi...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Hsin-Chou, Lin, Hsin-Chi, Huang, Mei-Chu, Li, Ling-Hui, Pan, Wen-Harn, Wu, Jer-Yuarn, Chen, Yuan-Tsong
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996943/
https://www.ncbi.nlm.nih.gov/pubmed/20602748
http://dx.doi.org/10.1186/1471-2164-11-415
_version_ 1782193240193105920
author Yang, Hsin-Chou
Lin, Hsin-Chi
Huang, Mei-Chu
Li, Ling-Hui
Pan, Wen-Harn
Wu, Jer-Yuarn
Chen, Yuan-Tsong
author_facet Yang, Hsin-Chou
Lin, Hsin-Chi
Huang, Mei-Chu
Li, Ling-Hui
Pan, Wen-Harn
Wu, Jer-Yuarn
Chen, Yuan-Tsong
author_sort Yang, Hsin-Chou
collection PubMed
description BACKGROUND: Allele frequency is one of the most important population indices and has been broadly applied to genetic/genomic studies. Estimation of allele frequency using genotypes is convenient but may lose data information and be sensitive to genotyping errors. RESULTS: This study utilizes a unified intensity-measuring approach to estimating individual-level allele frequencies for 1,104 and 1,270 samples genotyped with the single-nucleotide-polymorphism arrays of the Affymetrix Human Mapping 100K and 500K Sets, respectively. Allele frequencies of all samples are estimated and adjusted by coefficients of preferential amplification/hybridization (CPA), and large ethnicity-specific and cross-ethnicity databases of CPA and allele frequency are established. The results show that using the CPA significantly improves the accuracy of allele frequency estimates; moreover, this paramount factor is insensitive to the time of data acquisition, effect of laboratory site, type of gene chip, and phenotypic status. Based on accurate allele frequency estimates, analytic methods based on individual-level allele frequencies are developed and successfully applied to discover genomic patterns of allele frequencies, detect chromosomal abnormalities, classify sample groups, identify outlier samples, and estimate the purity of tumor samples. The methods are packaged into a new analysis tool, ALOHA (Allele-frequency/Loss-of-heterozygosity/Allele-imbalance). CONCLUSIONS: This is the first time that these important genetic/genomic applications have been simultaneously conducted by the analyses of individual-level allele frequencies estimated by a unified intensity-measuring approach. We expect that additional practical applications for allele frequency analysis will be found. The developed databases and tools provide useful resources for human genome analysis via high-throughput single-nucleotide-polymorphism arrays. The ALOHA software was written in R and R GUI and can be downloaded at http://www.stat.sinica.edu.tw/hsinchou/genetics/aloha/ALOHA.htm.
format Text
id pubmed-2996943
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-29969432010-12-07 A new analysis tool for individual-level allele frequency for genomic studies Yang, Hsin-Chou Lin, Hsin-Chi Huang, Mei-Chu Li, Ling-Hui Pan, Wen-Harn Wu, Jer-Yuarn Chen, Yuan-Tsong BMC Genomics Research Article BACKGROUND: Allele frequency is one of the most important population indices and has been broadly applied to genetic/genomic studies. Estimation of allele frequency using genotypes is convenient but may lose data information and be sensitive to genotyping errors. RESULTS: This study utilizes a unified intensity-measuring approach to estimating individual-level allele frequencies for 1,104 and 1,270 samples genotyped with the single-nucleotide-polymorphism arrays of the Affymetrix Human Mapping 100K and 500K Sets, respectively. Allele frequencies of all samples are estimated and adjusted by coefficients of preferential amplification/hybridization (CPA), and large ethnicity-specific and cross-ethnicity databases of CPA and allele frequency are established. The results show that using the CPA significantly improves the accuracy of allele frequency estimates; moreover, this paramount factor is insensitive to the time of data acquisition, effect of laboratory site, type of gene chip, and phenotypic status. Based on accurate allele frequency estimates, analytic methods based on individual-level allele frequencies are developed and successfully applied to discover genomic patterns of allele frequencies, detect chromosomal abnormalities, classify sample groups, identify outlier samples, and estimate the purity of tumor samples. The methods are packaged into a new analysis tool, ALOHA (Allele-frequency/Loss-of-heterozygosity/Allele-imbalance). CONCLUSIONS: This is the first time that these important genetic/genomic applications have been simultaneously conducted by the analyses of individual-level allele frequencies estimated by a unified intensity-measuring approach. We expect that additional practical applications for allele frequency analysis will be found. The developed databases and tools provide useful resources for human genome analysis via high-throughput single-nucleotide-polymorphism arrays. The ALOHA software was written in R and R GUI and can be downloaded at http://www.stat.sinica.edu.tw/hsinchou/genetics/aloha/ALOHA.htm. BioMed Central 2010-07-05 /pmc/articles/PMC2996943/ /pubmed/20602748 http://dx.doi.org/10.1186/1471-2164-11-415 Text en Copyright ©2010 Yang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yang, Hsin-Chou
Lin, Hsin-Chi
Huang, Mei-Chu
Li, Ling-Hui
Pan, Wen-Harn
Wu, Jer-Yuarn
Chen, Yuan-Tsong
A new analysis tool for individual-level allele frequency for genomic studies
title A new analysis tool for individual-level allele frequency for genomic studies
title_full A new analysis tool for individual-level allele frequency for genomic studies
title_fullStr A new analysis tool for individual-level allele frequency for genomic studies
title_full_unstemmed A new analysis tool for individual-level allele frequency for genomic studies
title_short A new analysis tool for individual-level allele frequency for genomic studies
title_sort new analysis tool for individual-level allele frequency for genomic studies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996943/
https://www.ncbi.nlm.nih.gov/pubmed/20602748
http://dx.doi.org/10.1186/1471-2164-11-415
work_keys_str_mv AT yanghsinchou anewanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT linhsinchi anewanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT huangmeichu anewanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT lilinghui anewanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT panwenharn anewanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT wujeryuarn anewanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT chenyuantsong anewanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT yanghsinchou newanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT linhsinchi newanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT huangmeichu newanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT lilinghui newanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT panwenharn newanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT wujeryuarn newanalysistoolforindividuallevelallelefrequencyforgenomicstudies
AT chenyuantsong newanalysistoolforindividuallevelallelefrequencyforgenomicstudies