multiClust: multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles

Clustering is carried out to identify patterns in transcriptomics profiles to determine clinically relevant subgroups of patients. Feature (gene) selection is a critical and an integral part of the process. Currently, there are many feature selection and clustering methods to identify the relevant genes and perform clustering of samples. However, choosing an appropriate methodology is difficult. In addition, extensive feature selection methods have not been supported by the available packages. Hence, we developed an integrative R-package called multiClust that allows researchers to experiment with the choice of combination of methods for gene selection and clustering with ease. Using multiClust, we identified the best performing clustering methodology in the context of clinical outcome. Our observations demonstrate that simple methods such as variance-based ranking perform well on the majority of data sets, provided that the appropriate number of genes is selected. However, different gene ranking and selection methods remain relevant as no methodology works for all studies.

AuthorNathan Lawlor [aut, cre], Peiyong Guan [aut], Alec Fabbri [aut], Krish Karuturi [aut], Joshy George [aut]
Date of publicationNone
MaintainerNathan Lawlor <nathan.lawlor03@gmail.com>
LicenseGPL (>= 2)
Version1.4.0

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Files

multiClust/DESCRIPTION
multiClust/NAMESPACE
multiClust/NEWS
multiClust/R
multiClust/R/WriteMatrixToFile.R multiClust/R/avg_probe_exp.R multiClust/R/cluster_analysis.R multiClust/R/input_file.R multiClust/R/nor.min.max.R multiClust/R/number_clusters.R multiClust/R/number_probes.R multiClust/R/probe_ranking.R multiClust/R/surv_analysis.R
multiClust/build
multiClust/build/vignette.rds
multiClust/inst
multiClust/inst/doc
multiClust/inst/doc/multiClust.R
multiClust/inst/doc/multiClust.Rmd
multiClust/inst/doc/multiClust.html
multiClust/inst/extdata
multiClust/inst/extdata/GSE2034-RFS-clinical-outcome.txt
multiClust/inst/extdata/GSE2034.normalized.expression.txt
multiClust/inst/extdata/GSE2034_Breast.SD_Rank.ward.D2.Fixed_Probe_Num.Fixed_Clust_Num.png
multiClust/inst/unitTests
multiClust/inst/unitTests/test_WriteMatrixToFile.R
multiClust/inst/unitTests/test_avg_probe_exp.R
multiClust/inst/unitTests/test_cluster_analysis.R
multiClust/inst/unitTests/test_input_file.R
multiClust/inst/unitTests/test_nor.min.max.R
multiClust/inst/unitTests/test_number_clusters.R
multiClust/inst/unitTests/test_number_probes.R
multiClust/inst/unitTests/test_probe_ranking.R
multiClust/inst/unitTests/test_surv_analysis.R
multiClust/man
multiClust/man/WriteMatrixToFile.Rd multiClust/man/avg_probe_exp.Rd multiClust/man/cluster_analysis.Rd multiClust/man/input_file.Rd multiClust/man/nor.min.max.Rd multiClust/man/number_clusters.Rd multiClust/man/number_probes.Rd multiClust/man/probe_ranking.Rd multiClust/man/surv_analysis.Rd
multiClust/tests
multiClust/tests/runTests.R
multiClust/vignettes
multiClust/vignettes/multiClust.Rmd

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