ABioTrans (link to paper) is a software tool that identifies gene expression variability through entropy and noise analyses. It is focused on commonly-used statistical techniques, namely, Pearson and Spearman rank correlations, Principal Component Analysis (PCA), k-means and hierarchical clustering, Shannon entropy, noise (square of coefficient of variation), differential expression (DE) analysis, and gene ontology classifications.
GeneCloudOmics allows the user to directly read RNA-Seq or Microarray data files, pre-process them and perform several statistical and data mining analyses. It provides easy options for multiple statistical distribution fitting, Pearson and Spearman rank correlations, PCA, k-means and hierarchical clustering, differential expression (DE) analysis, Shannon entropy and noise (square of the coefficient of variation) analyses, Entropy analysis, support vector machine (SVM) and Random Forest clustering, tSNE and SOM analyses.
GeneCloudOmics also provides several gene and protein datasets analyses such as gene ontology (GO) classifications, pathways enrichment, protein-protein interaction (PPI), subcellular localization, protein complex enrichment, protein domains annotation and Protein Sequence Download.
ScatLay (link to paper) identifies differential genes from gene expression data by using the overlap of 2 scatter plots. Plots are generated in log10 scale. The source code can be interacted via command-line interface.
ScatLay identifies differentially expressed genes by overlaying gene expression scatter plot of 2 different conditions on top of that of 2 replicates between the same condition. The non-overlapping genes are differentially expressed genes.