Evidence map›Paper›PMID 20602748›Full record

ArticleBMC genomics2010

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

Hsin-Chou Yang, Hsin-Chi Lin, Mei-Chu Huang, Ling-Hui Li, Wen-Harn Pan, Jer-Yuarn Wu, Yuan-Tsong Chen

Abstract read
In one paragraph

Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. SAQC: SNP array quality control.BMC bioinformatics · 2011
    Article
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Hsin-Chou YangInstitute of Statistical Science, Academia Sinica, Taipei 115, Taiwan. hsinchou@stat.sinica.edu.tw
Hsin-Chi Lin
Mei-Chu Huang
Ling-Hui Li
Wen-Harn Pan
Jer-Yuarn Wu
Yuan-Tsong Chen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAllele 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.

resultsThis 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).

conclusionsThis 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.

Indexed as

Gene FrequencyGenome, HumanGenomicsHumansPolymorphism, Single NucleotideSoftware

Identifiers

PMID20602748
PMCPMC2996943

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.