Weighted-SAMGSR: combining significance analysis of microarray-gene set reduction algorithm with pathway topology-based weights to select relevant genes.
BACKGROUND
It has been demonstrated that a pathway-based feature selection method that incorporates biological information within pathways during the process of feature selection usually outperforms a gene-based feature selection algorithm in terms of predictive accuracy and stability. Significance analysis of microarray-gene set reduction algorithm (SAMGSR), an extension to a gene set analysis method with further reduction of the selected pathways to their respective core subsets, can be regarded as a pathway-based feature selection method.


METHODS
In SAMGSR, whether a gene is selected is mainly determined by its expression difference between the phenotypes, and partially by the number of pathways to which this gene belongs. It ignores the topology information among pathways. In this study, we propose a weighted version of the SAMGSR algorithm by constructing weights based on the connectivity among genes and then combing these weights with the test statistics.


RESULTS
Using both simulated and real-world data, we evaluate the performance of the proposed SAMGSR extension and demonstrate that the weighted version outperforms its original version.﻿ CONCLUSIONS: To conclude, the additional gene connectivity information does faciliatate feature selection.


METHODS
This article was reviewed by Drs. Limsoon Wong, Lev Klebanov, and, I. King Jordan.
Division of Clinical Research, The First Hospital of Jilin University, 71Xinmin Street, Changchun, Jilin, China, 130021. stian@rockefeller.edu.|School of Mathematics, Jilin University, 2699 Qianjin Street, Changchun, Jilin, China, 130012. stian@rockefeller.edu.
Suyan
S
Tian
Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA, 30322, USA.
Howard H
HH
Chang
Department of Biostatistics, Markey Cancer Center, The University of Kentucky, 800 Rose St., Lexington, KY, 40536, USA.
Chi
C
Wang
Multiple sclerosis (MS); Non-small cell lung cancer (NSCLC); Pathway knowledge; Pathway-based feature selection; Significance analysis of microarray (SAM); Weighted gene expression profiles
Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545-50
16199517
BMC Syst Biol. 2011 Oct 12;5:161
21992556
Biometrics. 2013 Sep;69(3):582-93
23822182
J Bioinform Comput Biol. 2007 Oct;5(5):1139-53
17933015
J Stat Softw. 2010;33(1):1-22
20808728
Nucleic Acids Res. 2011 Jan;39(Database issue):D1002-4
21071405
BMC Bioinformatics. 2005 May 16;6:120
15904488
Chest. 2005 Jul;128(1):452-62
16002972
Bioinformatics. 2008 May 1;24(9):1175-82
18310618
Bioinformatics. 2012 May 1;28(9):1193-201
22423044
Bioinformatics. 2007 Oct 1;23(19):2507-17
17720704
Genome Biol. 2014 Feb 03;15(2):R29
24485249
Biostatistics. 2010 Apr;11(2):242-53
20097884
J Bioinform Comput Biol. 2015 Aug;13(4):1550018
26166210
J Bioinform Comput Biol. 2016 Aug;14(4):1650015
27102089
PLoS Comput Biol. 2016 Mar 09;12(3):e1004790
26960204
Mol Syst Biol. 2007;3:140
17940530
Bioinformatics. 2010 Sep 1;26(17):2136-44
20591905
Bioinformatics. 2013 Sep 1;29(17):2169-77
23842813
BMC Bioinformatics. 2005 Sep 21;6:233
16176585
BMC Bioinformatics. 2009 Jan 30;10 Suppl 1:S21
19208121
Nucleic Acids Res. 2003 Jan 1;31(1):258-61
12519996
Bioinformatics. 2013 Nov 15;29(22):2892-9
23966112
Bioinformatics. 2005 May 15;21(10):2394-402
15713736
BMC Bioinformatics. 2007 Feb 22;8:60
17316436
Biometrics. 2010 Jun;66(2):474-84
19645699
Proc Natl Acad Sci U S A. 2013 Apr 16;110(16):6388-93
23547110
BMC Bioinformatics. 2013 Apr 11;14:124
23578321
BMC Bioinformatics. 2010 May 20;11:271
20487548
BMC Bioinformatics. 2007 Jul 05;8:242
17612399
Proc Natl Acad Sci U S A. 2001 Apr 24;98(9):5116-21
11309499
Results Probl Cell Differ. 2010;51:259-85
20838962
Bioinformatics. 2009 Jul 1;25(13):1711-2
19398451
Bioinformatics. 2014 Jan 15;30(2):189-96
24292362
Brief Bioinform. 2009 Jan;10(1):24-34
18836208
PLoS One. 2014 Oct 15;9(10):e110052
25335090
Stat Sin. 2014 Jul;24(3):1433-1459
26316678