Using Gene-level to Generalize Transcript-level Classification Performance on Multiple Colorectal Cancer Microarray Studies

Hendrick Gao Min Lim, Yuan Chii Gladys Lee

研究成果: 書貢獻/報告類型會議貢獻

摘要

Several classification algorithms have been applied into microarray studies for colorectal cancer identification. Algorithms such as naïve bayes, random forest, logistic regression, support vector machine, and deep learning have been successfully used in previous studies. The accuracy of these algorithms shown promising result through n-fold validation. However, most of studies are limited to transcript-level that will implicate to biased interpretation of classification result due to different microarray platform entanglement. Therefore, we applied gene-level classification to generalize transcript-level classification result on multiple colorectal cancer microarray studies through different classification algorithms including: naïve Bayes, random forest, logistic regression, support vector machine, and deep learning. We evaluated classification performance using several parameters including: accuracy, area under ROC curve, recall and precision. As the result, we found biased classification result in transcript-level from multiple microarray studies can be solved through gene-level classification by applying annotation and merging. In addition, applying batch effect removal method can make gene-level classification performance slightly improved. Furthermore, annotation and merging also can be used to solve another biased result of feature selection in transcript-level.
原文英語
主出版物標題ICBBB 2020 - Proceedings of 2020 10th International Conference on Bioscience, Biochemistry and Bioinformatics
發行者Association for Computing Machinery, Inc
頁面64-68
頁數5
ISBN(電子)9781450376761
DOIs
出版狀態已發佈 - 一月 19 2020
事件10th International Conference on Bioscience, Biochemistry and Bioinformatics, ICBBB 2020 - Kyoto, 日本
持續時間: 一月 19 2020一月 22 2020

出版系列

名字ACM International Conference Proceeding Series

會議

會議10th International Conference on Bioscience, Biochemistry and Bioinformatics, ICBBB 2020
國家日本
城市Kyoto
期間1/19/201/22/20

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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