Evidence map›Paper›PMID 33118521›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2020

[An improved association analysis pipeline for tumor susceptibility variant in haplotype amplification area].

Yu Geng, Rongrong Yang, Jing Zhang

Open access · greenAbstract read
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Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Yu GengSchool of Health Management, Jinzhou Medical University, Jinzhou 121001, China.
Rongrong YangSchool of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Jing ZhangSchool of Health Management, Jinzhou Medical University, Jinzhou 121001, China.
Xi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveHaplotype amplification on germline variants is suggested to imply potential selective advantages and clonal expansion susceptibility and has become an important signature for seeking cancer susceptibility gene.Here we propose an improved association method that fully considers the haplotype amplification status.

methodsThe haplotype amplification status was estimated by the variant allelic frequencies.We adopted a permutation test on variant allelic frequencies to divide the candidate variants into multiple groups.A likelihood clustering method was then applied to establish the neighborhood system of the hidden Markov random field framework.A filtering pipeline was introduced into the proposed method to further refine the candidate variants, including a Wilson's interval filter and a false discovery rate controller.The final candidate set along with the haplotype amplification status was collapsed into the weighted virtual sites for association tests.

resultsThrough simulated tests on a series of datasets, we compared the type Ⅰ error rates of different minor allele frequencies, which stably fell within 2%, suggesting good robustness of the algorithm.In addition, we compared another 5 published association approaches for Type-Ⅰ and Type-Ⅱ error rates with the proposed method, which resulted in the error rates all within 2%, demonstrating significant advantages and a good statistical ability of the proposed method.

conclusionsThe proposed method can accurately identify tumor susceptibility variants in haplotype amplification area with good robustness and stability.

Indexed as

AlgorithmsNeoplasmsCluster AnalysisGene AmplificationGene FrequencyHaplotypesHumansPolymorphism, Single Nucleotidecancer genomicshaplotype amplificationrare variantsvariant association method

Identifiers

PMID33118521
PMCPMC7606235
OpenAlexW3096596424

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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.