Evidence map›Paper›PMID 19108714›Full record

ArticleBMC genetics2008

A large-scale survey of genetic copy number variations among Han Chinese residing in Taiwan.

Chien-Hsing Lin, Ling-Hui Li, Sheng-Feng Ho, Tzu-Po Chuang, Jer-Yuarn Wu, Yuan-Tsong Chen, Cathy S J Fann

Abstract read
In one paragraph

Article in BMC genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. MicroRNAs in Genetic Etiology of Human Diseases.Methods in molecular biology (Clifton, N.J.) · 2022
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Chien-Hsing LinDepartment of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan. eviliori.tw@yahoo.com.tw
Ling-Hui Li
Sheng-Feng Ho
Tzu-Po Chuang
Jer-Yuarn Wu
Yuan-Tsong Chen
Cathy S J Fann

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCopy number variations (CNVs) have recently been recognized as important structural variations in the human genome. CNVs can affect gene expression and thus may contribute to phenotypic differences. The copy number inferring tool (CNIT) is an effective hidden Markov model-based algorithm for estimating allele-specific copy number and predicting chromosomal alterations from single nucleotide polymorphism microarrays. The CNIT algorithm, which was constructed using data from 270 HapMap multi-ethnic individuals, was applied to identify CNVs from 300 unrelated Han Chinese individuals in Taiwan.

resultsUsing stringent selection criteria, 230 regions with variable copy numbers were identified in the Han Chinese population; 133 (57.83%) had been reported previously, 64 displayed greater than 1% CNV allele frequency. The average size of the CNV regions was 322 kb (ranging from 1.48 kb to 5.68 Mb) and covered a total of 2.47% of the human genome. A total of 196 of the CNV regions were simple deletions and 27 were simple amplifications. There were 449 genes and 5 microRNAs within these CNV regions; some of these genes are known to be associated with diseases.

conclusionThe identified CNVs are characteristic of the Han Chinese population and should be considered when genetic studies are conducted. The CNV distribution in the human genome is still poorly characterized, and there is much diversity among different ethnic populations.

Indexed as

Gene DosageGenome, HumanAlgorithmsAllelesAsian PeopleGene FrequencyGenetics, PopulationHumansMarkov ChainsMicroRNAsModels, GeneticOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideSoftwareTaiwanMicroRNAs

Identifiers

PMID19108714
PMCPMC2629477

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