Statistical methods of translating microarray data into clinically relevant diagnostic information in colorectal cancer

Bioinformatics
Byung Soo KimHyun Cheol Chung

Abstract

It is a common practice in cancer microarray experiments that a normal tissue is collected from the same individual from whom the tumor tissue was taken. The indirect design is usually adopted for the experiment that uses a common reference RNA hybridized both to normal and tumor tissues. However, it is often the case that the test material is not large enough for the experimenter to extract enough RNA to conduct the microarray experiment. Hence, collecting n cases does not necessarily end up with a matched pair sample of size n. Instead we usually have a matched pair sample of size n1, and two independent samples of sizes n2 and n3, respectively, for 'reference versus normal tissue only' and 'reference versus tumor tissue only' hybridizations (n=n1 + n2 + n3). Standard statistical methods need to be modified and new statistical procedures are developed for analyzing this mixed dataset. We propose a new test statistic, t3, as a means of combining all the information in the mixed dataset for detecting differentially expressed (DE) genes between normal and tumor tissues. We employed the extended receiver operating characteristic approach to the mixed dataset. We devised a measure of disagreement between a RT-PCR experiment and a ...Continue Reading

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Citations

Mar 4, 2009·Bioinformatics·Chen-An Tsai, James J Chen
Jul 23, 2013·PloS One·Wayne XuRobert Kratzke
Oct 11, 2011·PloS One·Mutsumi Kanamori-KatayamaYoshihide Hayashizaki
Oct 25, 2012·PloS One·Sjoerd M EuserJeroen W Den Boer
Apr 6, 2018·Statistical Methods in Medical Research·Qianya QiLili Tian
Dec 24, 2014·Cancer Informatics·Pei-Fen Kuan
May 18, 2019·Statistics in Medicine·Lubna AmroMarkus Pauly
Jul 10, 2021·Biometrical Journal. Biometrische Zeitschrift·Lubna AmroBurim Ramosaj

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