R-universe search: micrornaarray

Showing 5 of total 5 results (show query)

bioc

limma:Linear Models for Microarray and Omics Data

Data analysis, linear models and differential expression for omics data.

Maintained by Gordon Smyth. Last updated 5 days ago.

exonarray geneexpression transcription alternativesplicing differentialexpression differentialsplicing genesetenrichment dataimport bayesian clustering regression timecourse microarray micrornaarray mrnamicroarray onechannel proprietaryplatforms twochannel sequencing rnaseq batcheffect multiplecomparison normalization preprocessing qualitycontrol biomedicalinformatics cellbiology cheminformatics epigenetics functionalgenomics genetics immunooncology metabolomics proteomics systemsbiology transcriptomics

11.0 match 13.81 score 16k scripts 585 dependents

bioc

GEOexplorer:GEOexplorer: a webserver for gene expression analysis and visualisation

GEOexplorer is a webserver and R/Bioconductor package and web application that enables users to perform gene expression analysis. The development of GEOexplorer was made possible because of the excellent code provided by GEO2R (https: //www.ncbi.nlm.nih.gov/geo/geo2r/).

Maintained by Guy Hunt. Last updated 5 months ago.

software geneexpression mrnamicroarray differentialexpression microarray micrornaarray transcriptomics rnaseq

11.0 match 5 stars 5.32 score 14 scripts

bioc

AMARETTO:Regulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression

Integrating an increasing number of available multi-omics cancer data remains one of the main challenges to improve our understanding of cancer. One of the main challenges is using multi-omics data for identifying novel cancer driver genes. We have developed an algorithm, called AMARETTO, that integrates copy number, DNA methylation and gene expression data to identify a set of driver genes by analyzing cancer samples and connects them to clusters of co-expressed genes, which we define as modules. We applied AMARETTO in a pancancer setting to identify cancer driver genes and their modules on multiple cancer sites. AMARETTO captures modules enriched in angiogenesis, cell cycle and EMT, and modules that accurately predict survival and molecular subtypes. This allows AMARETTO to identify novel cancer driver genes directing canonical cancer pathways.

Maintained by Olivier Gevaert. Last updated 5 months ago.

statisticalmethod differentialmethylation generegulation geneexpression methylationarray transcription preprocessing batcheffect dataimport mrnamicroarray micrornaarray regression clustering rnaseq copynumbervariation sequencing microarray normalization network bayesian exonarray onechannel twochannel proprietaryplatforms alternativesplicing differentialexpression differentialsplicing genesetenrichment multiplecomparison qualitycontrol timecourse

11.0 match 4.88 score 15 scripts

bioc

randRotation:Random Rotation Methods for High Dimensional Data with Batch Structure

A collection of methods for performing random rotations on high-dimensional, normally distributed data (e.g. microarray or RNA-seq data) with batch structure. The random rotation approach allows exact testing of dependent test statistics with linear models following arbitrary batch effect correction methods.

Maintained by Peter Hettegger. Last updated 5 months ago.

software sequencing batcheffect biomedicalinformatics rnaseq preprocessing microarray differentialexpression geneexpression genetics micrornaarray normalization statisticalmethod

11.0 match 3.60 score 3 scripts

bioc

roastgsa:Rotation based gene set analysis

This package implements a variety of functions useful for gene set analysis using rotations to approximate the null distribution. It contributes with the implementation of seven test statistic scores that can be used with different goals and interpretations. Several functions are available to complement the statistical results with graphical representations.

Maintained by Adria Caballe. Last updated 5 months ago.

microarray preprocessing normalization geneexpression survival transcription sequencing transcriptomics bayesian clustering regression rnaseq micrornaarray mrnamicroarray functionalgenomics systemsbiology immunooncology differentialexpression genesetenrichment batcheffect multiplecomparison qualitycontrol timecourse metabolomics proteomics epigenetics cheminformatics exonarray onechannel twochannel proprietaryplatforms cellbiology biomedicalinformatics alternativesplicing differentialsplicing dataimport pathways

11.0 match 2.30 score