Evidence map›Paper›PMID 25569088›Full record

ArticleInternational journal of molecular sciences2015

Cloud computing-based TagSNP selection algorithm for human genome data.

Che-Lun Hung, Wen-Pei Chen, Guan-Jie Hua, Huiru Zheng, Suh-Jen Jane Tsai, Yaw-Ling Lin

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Che-Lun HungDepartment of Computer Science and Communication Engineering, Providence University, Taichung 43301, Taiwan. clhung@pu.edu.tw.
Wen-Pei ChenDepartment of Applied Chemistry, Providence University, Taiwan 43301, Taiwan. g1016008@pu.edu.tw.
Guan-Jie HuaDepartment of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan. gt758215@gmail.com.
Huiru ZhengSchool of Computing and Mathematics, University of Ulster, Newtownabbey BT37 0QB, UK. h.zheng@ulster.ac.uk.
Suh-Jen Jane TsaiDepartment of Applied Chemistry, Providence University, Taiwan 43301, Taiwan. sjtsai@pu.edu.tw.
Yaw-Ling LinDepartment of Applied Chemistry, Providence University, Taiwan 43301, Taiwan. yllin@pu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single nucleotide polymorphisms (SNPs) play a fundamental role in human genetic variation and are used in medical diagnostics, phylogeny construction, and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Haplotypes are regions of linked genetic variants that are closely spaced on the genome and tend to be inherited together. Genetics research has revealed SNPs within certain haplotype blocks that introduce few distinct common haplotypes into most of the population. Haplotype block structures are used in association-based methods to map disease genes. In this paper, we propose an efficient algorithm for identifying haplotype blocks in the genome. In chromosomal haplotype data retrieved from the HapMap project website, the proposed algorithm identified longer haplotype blocks than an existing algorithm. To enhance its performance, we extended the proposed algorithm into a parallel algorithm that copies data in parallel via the Hadoop MapReduce framework. The proposed MapReduce-paralleled combinatorial algorithm performed well on real-world data obtained from the HapMap dataset; the improvement in computational efficiency was proportional to the number of processors used.

Indexed as

AlgorithmsComputational BiologyGenome, HumanGenome-Wide Association StudyHaplotypesHumansLinkage DisequilibriumPolymorphism, Single Nucleotide

Identifiers

PMID25569088
PMCPMC4307292

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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.