Different methods have been proposed for analyzing differentially expressed (DE) genes in microarray data. Methods based on statistical tests that incorporate expression level variability are used more commonly than those based on fold change (FC).…

Different methods have been proposed for analyzing differentially expressed (DE) genes in microarray data. Methods based on statistical tests that incorporate expression level variability are used more commonly than those based on fold change (FC). However, FC based results are more reproducible and biologically relevant.

Provides an integrated solution for analysing data from gene expression…

Provides an integrated solution for analysing data from gene expression experiments. limma contains rich features for handling complex experimental designs and for information borrowing to overcome…

Allows researchers to use prior information on groupings of genes and to…

Allows researchers to use prior information on groupings of genes and to specifically investigate groups of genes that interest them from a biological point of view. When researchers have many…

A web application for the functional analysis of gene expression and genomic…

A web application for the functional analysis of gene expression and genomic data. Babelomics offers user-friendly access to a full range of methods that cover: (i) primary data analysis, (ii) a…

A package specifically suited for the analysis of time-course gene expression…

A package specifically suited for the analysis of time-course gene expression data, which was developed originally for microarrays and hence was limited in its application to count data. Updated…

A differential expression framework that capitalizes on the high number of…

A differential expression framework that capitalizes on the high number of concurrent measurements. It extends to various experimental designs and target categories (transcripts, genes, genomic…

Analyzes genome-wide expression patterns in one experiment at a time.…

Analyzes genome-wide expression patterns in one experiment at a time. T-profiler is a web application that uses the t-test to score the difference between the mean expression level of predefined…

Aims to identify biological processes that are consistently deregulated across…

Aims to identify biological processes that are consistently deregulated across a broad set of microarray experiments associated with different disease models in both animal and human tissues. GNEA…

Uses the Earth moverâ€™s distance to measure the overall difference between the…

Uses the Earth moverâ€™s distance to measure the overall difference between the distributions of a geneâ€™s expression in two classes of samples and uses permutations to obtain q-values for each…

Captures single impulse-like progression patterns in high throughput time…

Captures single impulse-like progression patterns in high throughput time series datasets. ImpulseDE can be applied on any kind of high throughput gene expression data. It reports differentially…

Analyses sparse and heterogeneous time course data with high detection…

Analyses sparse and heterogeneous time course data with high detection sensitivity and transparency. TTCA is specifically designed for the analysis of perturbation responses. It combines different…

A package for ranking differentially expressed gene expression time courses…

A package for ranking differentially expressed gene expression time courses through Gaussian process regression. gprege fits two GPs with the an RBF (+ noise diagonal) kernel on each profile. One GP…

Provides posterior distributions of gene expression indices and other…

Provides posterior distributions of gene expression indices and other quantities of interest rather than point estimates. BGX is a Bayesian hierarchical model for the analysis of Affymetrix GeneChip…

Analyses Gene Expression Omnibus (GEO) datasets. GeoDiver is a web application…

Analyses Gene Expression Omnibus (GEO) datasets. GeoDiver is a web application which performs Differential Gene Expression Analysis (DGEA) and Generally Applicable Gene-set Enrichment Analysis (GAGE)…

Evaluates cellular engineering processes in a systemic rather than marker-based…

Evaluates cellular engineering processes in a systemic rather than marker-based fashion. eegc integrates transcriptome profiling and functional analysis. It clusters genes into categories…

An R package for systematically assessing the difference in gene-gene…

An R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. DGCA contains functions to filter, process, save, visualize, and interpret…

Infers cell type-specific expression based on co-expression similarity with…

Infers cell type-specific expression based on co-expression similarity with known cell type marker genes. CellMapper is an R package that can make accurate predictions using publicly available…

An integrated software platform for the analysis of microarray gene expression…

An integrated software platform for the analysis of microarray gene expression data. EXPANDER is designed to support all the stages of microarray data analysis, from raw data normalization to…

A model-free shrinkage estimate of the variance vector across genes. Shrinkage…

A model-free shrinkage estimate of the variance vector across genes. Shrinkage t is derived in a quasi-empirical Bayes setting. The new rank score is fully automatic and requires no specification of…

Identifies gene modules of coordinated differential methylation and…

Identifies gene modules of coordinated differential methylation and differential expression in the context of a human interactome. FEM is a functional supervised algorithm that could be applied to…

Implements Partial Least Squares regression to extract the hidden signals of…

Implements Partial Least Squares regression to extract the hidden signals of sample-specific heterogeneity in the data and uses them to find the genes that are actually correlated with the phenotype…

Builds a sparse differential network based on partial correlation for better…

Builds a sparse differential network based on partial correlation for better visualization, and integrates differential expression (DE) and differential network (DN) analyses for biomarker discovery.…

Allows to analyze large-scale RNA-seq studies. MDSeq utilizes a novel…

Allows to analyze large-scale RNA-seq studies. MDSeq utilizes a novel re-parametrization of the negative binomial to permit for robust statistical inference and efficient computations of the…

Integrates transcriptional expression data and genomic annotations to identify…

Integrates transcriptional expression data and genomic annotations to identify groups of physically contiguous genes characterized by regional differential expression in bacterial genomes. WoPPER Is…

An open source, point-and-click software program for the significance analysis…

An open source, point-and-click software program for the significance analysis of DNA microarray experiments. EDGE can perform both standard and time course differential expression analysis. The…

A multi-step statistical framework that uses latent variable analysis to…

A multi-step statistical framework that uses latent variable analysis to analyze differential expression from mixture samples. This approach is based on latent variable analysis and is…

Explores the linear decision boundary family. DiscriminantCut is a machine…

Explores the linear decision boundary family. DiscriminantCut is a machine learning methodology for robust differential expression analysis, which can be an avenue to significantly advance research…

A statistical approach based on partial least squares regression to infer the…

A statistical approach based on partial least squares regression to infer the true TFAs from a combination of mRNA expression and DNA-protein binding measurements. Plsgenomics is also statistically…

A system, easy to use even with no pre-existing knowledge, to identify gene…

A system, easy to use even with no pre-existing knowledge, to identify gene sets with monotonic expression patterns in multi-stage as well as in time-series genomics matrices. The case studies on…

Assess the significance of gene effects in comparative experiments. cDNA…

Assess the significance of gene effects in comparative experiments. cDNA Microarray Analysis is based on a hierarchical model that incorporates several levels of variations. A version of empirical…

Uses a simple univariate normal-uniform mixture model, in combination with new…

Uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization. NUDGE is a simple method to find…

A differentially expressed (DE) gene selection algorithm, which controls the…

A differentially expressed (DE) gene selection algorithm, which controls the FDR based on predictive Bayesian estimates. The simulation studies empirically showed that the proposed confident…

Implements a wavelet-based model for analyzing transcriptome data and extends…

Implements a wavelet-based model for analyzing transcriptome data and extends it towards more complex experimental designs. With waveTiling, the user is able to discover group-wise expressed regions,…

Investigates and optimizes the performance of three statistical approaches by…

Investigates and optimizes the performance of three statistical approaches by using simulated and experimental data sets with varying numbers of missing values. LimmaRP uses three tools, including…

Differences gene expression. BGmix uses a C++ routine to fit the chosen model…

Differences gene expression. BGmix uses a C++ routine to fit the chosen model via an Markov chain Monte Carlo (MCMC) algorithm. Files are written to a sub-directory in the working directory. The tool…

Performs compatibly in detecting the shape of the local false discovery rate.…

Performs compatibly in detecting the shape of the local false discovery rate. TWILIGHT includes several functions for the statistical analysis of two-condition microarray data. TWILIGHT has a smaller…

Provides a set of tools for analyzing data from a factorial designed microarray…

Provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions of factDesign can be…

A package for analysis of microarray data using a linear model and glog data…

A package for analysis of microarray data using a linear model and glog data transformation. LMGene allows the identification of Differentially Expressed Genes in Gene Expression Arrays.

Contains functions that calculates various statistics of differential…

Contains functions that calculates various statistics of differential expression for microarray data, including t statistics, fold change, F statistics, SAM, moderated t and F statistics and B…

Allows to characterize the operating characteristics of a microarray…

Allows to characterize the operating characteristics of a microarray experiment, i.e. the trade-off between false discovery rate and the power to detect truly regulated genes. OCplus includes tools…

A package offering test for differentially expressed genes with microarray…

A package offering test for differentially expressed genes with microarray data. Bridge can be used with both cDNA microarrays or Affymetrix chip. It fits a robust Bayesian hierarchical model for…

A package based on a Laplace mixture modelling of microarray experiments. A…

A package based on a Laplace mixture modelling of microarray experiments. A hierarchical Bayesian approach is used, and the hyperparameters are estimated using empirical Bayes. The main purpose of…

Models the variance-versus-mean dependence that exists in a variety of…

Models the variance-versus-mean dependence that exists in a variety of genome-wide datasets, including microarray and proteomics data. PLGEM improves the detection of differentially expressed genes…

A library used to do significance analysis of microarray data with small number…

A library used to do significance analysis of microarray data with small number of replicates. LPE uses resampling based FDR adjustment, and gives less conservative results than traditional…

Provides a comprehensive set of functionalities that together facilitate the…

Provides a comprehensive set of functionalities that together facilitate the exploration, assessment and deconvolution of gene expression data generated from heterogeneous biological samples. It…

A statistically rigorous gene set test that allows for gene-wise correlation…

A statistically rigorous gene set test that allows for gene-wise correlation while being applicable to almost any experimental design. Instead of permutation, ROAST uses rotation, a Monte Carlo…

Determines if the observed gene regulation is the result of changes in the…

Determines if the observed gene regulation is the result of changes in the cellular make up of the sample. CTen can distinguish between active gene transcription and apparent gene expression…

Encodes the physical design of the microarray and contain the sequence details…

Encodes the physical design of the microarray and contain the sequence details to link the oligonucleotide probes of the chip to the interrogated transcripts. CDFs is a set of custom for Affymetrix…

A statistical testing procedure that further improves upon current methods by…

A statistical testing procedure that further improves upon current methods by incorporating the well-documented relationship between the absolute gene expression level and the variance of gene…

Helps to perform gene expression analysis. Nexus Expression provides an…

Helps to perform gene expression analysis. Nexus Expression provides an interface which allows to visualize and explore microarray or RNA-Seq data. The interface merges sample phenotypes with gene…

A package to identify differentially expressed genes in microarray time-course…

A package to identify differentially expressed genes in microarray time-course data. BETR explicitly uses the time-dependent structure of the data, employing an empirical Bayes procedure to stabilize…

A process for the creation of library tags that increases accuracy in…

A process for the creation of library tags that increases accuracy in identification of the source tissue with little processing time overhead. UITagCreator also identifies the tissue of origin…

Provides the academic community with free and reliable web tools for…

Provides the academic community with free and reliable web tools for Bioinformatics and Genome research. GEDA provides a gene expression data analysis tool. The GEDA tool calculates the averages of…