You can code your software in Python and use scikit learn (sklearn) library.

Have a look here for documentation:

http://scikit-learn.org/stable/modules/clustering.html

http://scikit-learn.org/stable/modules/clustering.html

Mariia

http://biit.cs.ut.ee/clustvis/

TRANSCRIPTOMICS

GEPAS (Gene Expression Pattern Analysis Suite) - an experiment-oriented pipeline for the analysis of microarray gene expression data. It contains an incredible number of tools for normalization, preprocessing, viewing, clustering, differential expression, supervised classification, and data mining & analysis. (Reference: J.M. Vaquerizas et al. 2005. Nucl. Acids Res. 33: W616-W620).

Cyber-T (National Center for Genomic Resources, U.S.A.) if you have 2-dye data (such as what would be generated by the usual glass slide arrays probed with cy3/cy5-labelled cDN) use PAIRED DATA, while Control+Experimental is for those with Affymetrix-based data consisting of a separate control and experimental arrays.

NIA Array Analysis Tool - for microarray data analysis, which features the false discovery rate for testing statistical significance and the principal component analysis using the singular value decomposition method for detecting the global trends of gene-expression patterns. Additional features include: analysis of variance with multiple methods for error variance adjustment, correction of cross-channel correlation for two-color microarrays, identification of genes specific to each cluster of tissue samples, biplot of tissues and corresponding tissue-specific genes, clustering of genes that are correlated with each principal component (PC), and three-dimensional graphics. (Reference: A.A. Sharov et al. 2005. Bioinformatics 21: 2548-2549).

M@CBETH - MicroArray Classification Benchmarking Tool on Host server - offers the microarray community a simple tool for making optimal two-class predictions by by using randomizations of the benchmarking dataset. Registration is required in order to use this service. (Reference:  N.L.M.M. Pochet et al. 2005. Bioinformatics 21: 3185 - 3186).

MicroArray Genome Imaging & Clustering Tool (MAGIC Tool) - A JAVA teaching resource developed at Davidson College (U.S.A.) by Laurie Heyer and her undergraduate students (Reference: L. J. Heyer et al. 2005. Bioinformatics 21: 2114 - 2115).

VAMPIRE microarray analysis suite - is a statistical framework that models the dependence of measurement variance on the level of gene expression in the context of a Bayesian hierarchical model. (Reference: A. Hsiao et al. 2005. Nucl. Acids Res. 33: W627-W632).

GEMS - Gene Expression Mining Server - simple but promising new approach for biclustering based on a Gibbs sampling paradigm. (Reference: C.-J. Wu et al. 2004. Genome Informatics 15: 239-248).  

http://chemmine.ucr.edu/

http://www.ncss.com/software/ncss/clustering-in-ncss/

clustering approaches in R is much more easier and it is a freely available software with many tutorials avail online. When we think of clustering your results cluster patients according to microRNA, mRNA expression level, gene amplification.

hierarchical clustering is one of the recommendable method.

Use

library(vegan)

b

R should be your best choice...there are several in-build packages for clustering in R software...it is also freely available....you can also build your code in java using Weka software.....But R is widely used now-a-days for machine learning applications...

As suggested by Prof. Sanjay R is the best choice with a great open source community. However your field is very specific , please c if the below view is useful

https://cran.r-project.org/web/views/Genetics.html

R is the best SW for your project. Matlab is better if you have a licencse.

you can used weka

http://www.cs.waikato.ac.nz/ml/weka/

Statistica is a very good package for carrying out cluster analysis.

Also, it can be done using Matlab.

You can use SPSS program

Try Past 3.x

http://folk.uio.no/ohammer/past/

I really like ClustVis as Dinesh suggested, although it's PCA + Clustering, not really K Means. I tried a few free online one tonight. They were worthless. No info on suggested format or how to use / plot / interpret their output (ToolSlick, SciStatCalc). ToolSlick site was very difficult to navigate to figure out which "tools" they had. Most folks don't want to do any programming! They just want to input their data and see what patterns there are.

I would say XLSTATfor PCA or Cluster analyses, one of the best powerful programs nicely fitted with excel as addon.

I would say XLSTATfor PCA or Cluster analyses, one of the best powerful programs nicely fitted with excel as addon it is not free

Yes, Tableau. (or R for advanced users)

I use both

You can use this tool freely. This tool exploits a multi objective heuristic algorithm to clusters the modules of source code.

http://savalan-smct.com/

ClustVis: a web tool for visualizing clustering of multivariate data (BETA)

https://biit.cs.ut.ee/clustvis/

Dear Mariia Inomistova . See the following useful link: https://www.kdnuggets.com/software/clustering.html

Kindly see also the following useful link: https://us.sios.com/what-we-do/clustering-software/

Also check please the following useful link: https://www.ncss.com/software/ncss/clustering-in-ncss/

The following RG link is also very good: Article ClusterEnG: an interactive educational web resource for clus...