Literature DB >> 31115892

ROC Curves for the Statistical Analysis of Microarray Data.

Ricardo Cao1, Ignacio López-de-Ullibarri2.   

Abstract

A receiver operating characteristic (ROC) curve is a graphical plot that illustrates the diagnostic ability of a binary classifier as a function of its discrimination threshold. This chapter is an overview on the use of ROC curves for microarray data. The notion of ROC curve and its motivation is introduced in Subheading 1. Relevant scientific contributions concerning the use of ROC curves for microarray data are briefly reviewed in Subheading 2. The special case with covariates is considered in Subheading 3. Two relevant aspects are reviewed in this section: the use of LASSO techniques for selecting and combining relevant markers and how to correct for multiple testing when a large number of markers are available. Finally, some conclusions are included.

Keywords:  AUC; FDR; FWER; LASSO; Microarray; Multiple testing; ROC curve; pAUC

Year:  2019        PMID: 31115892     DOI: 10.1007/978-1-4939-9442-7_11

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  6 in total

1.  A practical method to screen and identify functioning biomarkers in nasopharyngeal carcinoma.

Authors:  Chengyou Liu; Peijie Guo; Leilei Zhou; Yuhe Wang; Shuchang Tian; Yong Ding; Jing Wu; Junlin Zhu; Yu Wang
Journal:  Sci Rep       Date:  2021-03-31       Impact factor: 4.379

2.  Utility of Liver Function Tests and Fatty Liver Index to Categorize Metabolic Phenotypes in a Mediterranean Population.

Authors:  Dariusz Narankiewicz; Josefina Ruiz-Nava; Veronica Buonaiuto; María Isabel Ruiz-Moreno; María Dolores López-Carmona; Luis Miguel Pérez-Belmonte; Ricardo Gómez-Huelgas; María Rosa Bernal-López
Journal:  Int J Environ Res Public Health       Date:  2020-05-18       Impact factor: 3.390

3.  Prediction and analysis of novel key genes ITGAX, LAPTM5, SERPINE1 in clear cell renal cell carcinoma through bioinformatics analysis.

Authors:  Yingli Sui; Kun Lu; Lin Fu
Journal:  PeerJ       Date:  2021-04-20       Impact factor: 2.984

4.  Identification of Diagnostic Markers Correlated With HIV+ Immune Non-response Based on Bioinformatics Analysis.

Authors:  Ruojing Bai; Zhen Li; Yuying Hou; Shiyun Lv; Ran Wang; Wei Hua; Hao Wu; Lili Dai
Journal:  Front Mol Biosci       Date:  2021-12-22

5.  Construction and validation of a novel gene signature for predicting the prognosis of osteosarcoma.

Authors:  Jinpo Yang; Anran Zhang; Huan Luo; Chao Ma
Journal:  Sci Rep       Date:  2022-01-24       Impact factor: 4.996

6.  Bioinformatics searching of diagnostic markers and immune infiltration in polycystic ovary syndrome.

Authors:  Xinrui Yao; Xiuxia Wang
Journal:  Front Genet       Date:  2022-08-31       Impact factor: 4.772

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.