Search Results for "gene"

clusterProfiler is an R/Bioconductor package that provides a unified workflow for functional enrichment analysis to interpret high-throughput omics results. It supports both over-representation analysis and gene set enrichment analysis, letting you work with unranked gene lists or ranked statistics from differential pipelines. The package connects to multiple knowledge bases—such as Gene Ontology, KEGG, Reactome, Disease Ontology, MeSH and others—through a consistent interface so you can query different biological lenses without rewriting code. ...

The OpenGEREA is a open enrichment analysis framework for gene expression regulation data analysis.

Capabilities of CorNetMap: 1. Read data as tab-delimited text file. Can be used for analysis of any data set beyond gene expression. 2. Capable of both two-dimensional and multidimensional data analysis. 3. Calculate Pearson correlation and cross-correlation for analysis data with phase difference. 4. Generate correlation Heat-map and draws network map. 5. Save correlation data as text file. How to use and doccumentation: https://sourceforge.net/projects/cornetmap/files/Documentation_corNetMap.pdf Sample data for testing: https://sourceforge.net/projects/cornetmap/files/Test%20Data/ Citation: Cite CornetMap as " Khaund, A. ...

RNA-seq analysis is becoming a standard method for global gene expression profiling. However, open and standard pipelines to perform RNA-seq analysis by non-experts remain challenging due to the large size of the raw data files and the hardware requirements for running the alignment step. Here we introduce a reproducible open source RNA-seq pipeline delivered as an IPython notebook and a Docker image.

Massively parallel sequencing of cDNA reverse transcribed from RNA (RNASeq) provides an accurate estimate of the quantity and composition of mRNAs. To characterize the transcriptome through the analysis of RNA-seq data, we developed PRADA. PRADA focuses on the processing and analysis of gene expression estimates, supervised and unsupervised gene fusion identification, and supervised intragenic deletion identification. PRADA currently supports 7 modules to process and identify abnormalities from RNAseq data: preprocess: Generates aligned and recalibrated BAM files. expression: Generates gene expression (RPKM) and quality metrics. ...

TOPS provides the benchtop scientist with a free toolset to analyze, filter and visualize data from functional genomic gene-gene and gene-drug interaction screens with a flexible interface to accommodate various different technologies and analysis algorithms in addition to those already provided here.

Automated Microarray Data Analysis

BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).

GSCope3 performs microarray data analysis to find correlations between BLSOM clusters and any form of omic knowledge expressed in OSML. Includes example metabolic pathway, gene ontology, genome position, transcription and PPI knowledge in OSML format.

GEDAS is a software to perform microarray data analysis with friendly user interface and convenient data display. Currently some commonly used data clustering algorithms have been implemented in this software.

BIRBU (BIological Relationship BUilder) is a Java tool for microarray gene expression data analysis. BIRBU identifies biologically significant relationship between genes using microarray data and prior knowledge on relationships between genes.