A sparse negative binomial classifier with covariate adjustment for RNA-seq data-Reference-Cited by-同舟云学术

A sparse negative binomial classifier with covariate adjustment for RNA-seq data

Published:2022-06-01 Issue:2 Volume:16 Page:
ISSN:1932-6157
Container-title:The Annals of Applied Statistics
language:
Short-container-title:Ann. Appl. Stat.

Author:

Rahman Tanbin¹,Huang Hsin-En²,Li Yujia¹,Tai An-Shun²,Hseih Wen-Ping²,McClung Colleen A.³,Tseng George¹

Affiliation:

1. Department of Biostatistics, University of Pittsburgh

2. Institute of Statistics, National Tsing Hua University

3. Deparment of Psychiatry, University of Pittsburgh

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Reference29 articles.

1. BALZAMINO, B. O., ESPOSITO, G., MARINO, R., KELLER, F. and MICERA, A. (2015). NGF expression in reelin-deprived retinal cells: A potential neuroprotective effect. Neuromol. Med. 17 314–325.

2. BRADLEY, A. P. (1997). The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit. 30 1145–1159.

3. BROWN, M. P., GRUNDY, W. N., LIN, D., CRISTIANINI, N., SUGNET, C. W., FUREY, T. S., ARES, M. and HAUSSLER, D. (2000). Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Natl. Acad. Sci. USA 97 262–267.

4. BULLARD, J. H., PURDOM, E., HANSEN, K. D. and DUDOIT, S. (2010). Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinform. 11 94.

5. CHU, Y. and COREY, D. R. (2012). RNA sequencing: Platform selection, experimental design, and data interpretation. Nucleic. Acid Ther. 22 271–274. PMID: 22830413.