HDG-select: A Novel GUI Based Application for Gene Selection and Classification in High Dimensional Datasets

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2021 Jan 28

PMID 33507983

Citations 2

Authors

Shilan S Hameed

Rohayanti Hassan

Wan Haslina Hassan

Fahmi F Muhammadsharif

Liza Abdul Latiff

Affiliations

Soon will be listed here.

Abstract

The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical researchers and end users is of great importance. In this work, a novel stand-alone application, which is based on graphical user interface (GUI), is developed to perform the full functionality of gene selection and classification in high dimensional datasets. The so-called HDG-select application is validated on eleven high dimensional datasets of the format CSV and GEO soft. The proposed tool uses the efficient algorithm of combined filter-GBPSO-SVM and it was made freely available to users. It was found that the proposed HDG-select outperformed other tools reported in literature and presented a competitive performance, accessibility, and functionality.

Citing Articles

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References

Diaz-Uriarte R . GeneSrF and varSelRF: a web-based tool and R package for gene selection and classification using random forest. BMC Bioinformatics. 2007; 8:328. PMC: 2034606. DOI: 10.1186/1471-2105-8-328. View

Barash E, Sal-Man N, Sabato S, Ziv-Ukelson M . BacPaCS-Bacterial Pathogenicity Classification via Sparse-SVM. Bioinformatics. 2018; 35(12):2001-2008. DOI: 10.1093/bioinformatics/bty928. View

El-Fishawy P, State M . The genetics of autism: key issues, recent findings, and clinical implications. Psychiatr Clin North Am. 2010; 33(1):83-105. PMC: 2841771. DOI: 10.1016/j.psc.2009.12.002. View

WILCOXIN F . Probability tables for individual comparisons by ranking methods. Biometrics. 1947; 3(3):119-22. View

Alter M, Kharkar R, Ramsey K, Craig D, Melmed R, Grebe T . Autism and increased paternal age related changes in global levels of gene expression regulation. PLoS One. 2011; 6(2):e16715. PMC: 3040743. DOI: 10.1371/journal.pone.0016715. View

Diaz-Uriarte R, de Andres S . Gene selection and classification of microarray data using random forest. BMC Bioinformatics. 2006; 7:3. PMC: 1363357. DOI: 10.1186/1471-2105-7-3. View

Hira Z, Gillies D . A Review of Feature Selection and Feature Extraction Methods Applied on Microarray Data. Adv Bioinformatics. 2015; 2015:198363. PMC: 4480804. DOI: 10.1155/2015/198363. View

Lazar C, Taminau J, Meganck S, Steenhoff D, Coletta A, Molter C . A survey on filter techniques for feature selection in gene expression microarray analysis. IEEE/ACM Trans Comput Biol Bioinform. 2012; 9(4):1106-19. DOI: 10.1109/TCBB.2012.33. View

Jirapech-Umpai T, Aitken S . Feature selection and classification for microarray data analysis: evolutionary methods for identifying predictive genes. BMC Bioinformatics. 2005; 6:148. PMC: 1181625. DOI: 10.1186/1471-2105-6-148. View

10.

Annavarapu C, Dara S, Banka H . Cancer microarray data feature selection using multi-objective binary particle swarm optimization algorithm. EXCLI J. 2016; 15:460-473. PMC: 5083964. DOI: 10.17179/excli2016-481. View

11.

Alon U, Barkai N, Notterman D, Gish K, Ybarra S, Mack D . Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc Natl Acad Sci U S A. 1999; 96(12):6745-50. PMC: 21986. DOI: 10.1073/pnas.96.12.6745. View

12.

Lai C, Reinders M, Vant Veer L, Wessels L . A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets. BMC Bioinformatics. 2006; 7:235. PMC: 1569875. DOI: 10.1186/1471-2105-7-235. View

13.

Saeys Y, Inza I, Larranaga P . A review of feature selection techniques in bioinformatics. Bioinformatics. 2007; 23(19):2507-17. DOI: 10.1093/bioinformatics/btm344. View

14.

Kaya H, Hasman H, Larsen J, Stegger M, Johannesen T, Allesoe R . SCCFinder, a Web-Based Tool for Typing of Staphylococcal Cassette Chromosome in Using Whole-Genome Sequence Data. mSphere. 2018; 3(1). PMC: 5812897. DOI: 10.1128/mSphere.00612-17. View

15.

Latkowski T, Osowski S . Computerized system for recognition of autism on the basis of gene expression microarray data. Comput Biol Med. 2014; 56:82-8. DOI: 10.1016/j.compbiomed.2014.11.004. View

16.

Glaab E, Garibaldi J, Krasnogor N . ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization. BMC Bioinformatics. 2009; 10:358. PMC: 2776026. DOI: 10.1186/1471-2105-10-358. View

17.

Tamazian G, Dobrynin P, Krasheninnikova K, Komissarov A, Koepfli K, OBrien S . Chromosomer: a reference-based genome arrangement tool for producing draft chromosome sequences. Gigascience. 2016; 5(1):38. PMC: 4994284. DOI: 10.1186/s13742-016-0141-6. View

18.

Bridge P, Sawilowsky S . Increasing physicians' awareness of the impact of statistics on research outcomes: comparative power of the t-test and and Wilcoxon Rank-Sum test in small samples applied research. J Clin Epidemiol. 1999; 52(3):229-35. DOI: 10.1016/s0895-4356(98)00168-1. View

19.

Govindarajan R, Duraiyan J, Kaliyappan K, Palanisamy M . Microarray and its applications. J Pharm Bioallied Sci. 2012; 4(Suppl 2):S310-2. PMC: 3467903. DOI: 10.4103/0975-7406.100283. View

20.

Duez M, Giraud M, Herbert R, Rocher T, Salson M, Thonier F . Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing. PLoS One. 2016; 11(11):e0166126. PMC: 5106020. DOI: 10.1371/journal.pone.0166126. View