• Title/Summary/Keyword: Genome research

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Comparative Statistic Module (CSM) for Significant Gene Selection

  • Kim, Young-Jin;Kim, Hyo-Mi;Kim, Sang-Bae;Park, Chan;Kimm, Kuchan;Koh, InSong
    • Genomics & Informatics
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    • v.2 no.4
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    • pp.180-183
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    • 2004

  • Comparative Statistic Module(CSM) provides more reliable list of significant genes to genomics researchers by offering the commonly selected genes and a method of choice by calculating the rank of each statistical test based on the average ranking of common genes across the five statistical methods, i.e. t-test, Kruskal-Wallis (Wilcoxon signed rank) test, SAM, two sample multiple test, and Empirical Bayesian test. This statistical analysis module is implemented in Perl, and R languages.

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HapAnalyzer: Minimum Haplotype Analysis System for Association Studies

  • Jung, Ho-Youl;Park, Jung-Sun;Park, Yun-Ju;Kim, Young-Jin;Kimm, Kuchan;Koh, InSong
    • Genomics & Informatics
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    • v.2 no.2
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    • pp.107-109
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    • 2004

  • HapAnalyzer is an analysis system that provides minimum analysis methods for the SNP-based association studies. It consists of Hardy-Weinberg equilibrium (HWE) test, linkage disequilibrium (LD) computation, haplotype reconstruction, and SNP (or haplotype)-phenotype association assessment. It is well suited to a case-control association study for the unrelated population.

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Generation of Whole-Genome Sequencing Data for Comparing Primary and Castration-Resistant Prostate Cancer

  • Park, Jong-Lyul;Kim, Seon-Kyu;Kim, Jeong-Hwan;Yun, Seok Joong;Kim, Wun-Jae;Kim, Won Tae;Jeong, Pildu;Kang, Ho Won;Kim, Seon-Young
    • Genomics & Informatics
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    • v.16 no.3
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    • pp.71-74
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    • 2018

  • Because castration-resistant prostate cancer (CRPC) does not respond to androgen deprivation therapy and has a very poor prognosis, it is critical to identify a prognostic indicator for predicting high-risk patients who will develop CRPC. Here, we report a dataset of whole genomes from four pairs of primary prostate cancer (PC) and CRPC samples. The analysis of the paired PC and CRPC samples in the whole-genome data showed that the average number of somatic mutations per patients was 7,927 in CRPC tissues compared with primary PC tissues (range, 1,691 to 21,705). Our whole-genome sequencing data of primary PC and CRPC may be useful for understanding the genomic changes and molecular mechanisms that occur during the progression from PC to CRPC.

  • https://doi.org/10.5808/GI.2018.16.3.71 인용 PDF KSCI