Tools   Select Another Resource Report Type

https://bioconductor.org/packages/Orthology.eg.db/

Software R package to provide orthology mappings between species, based on NCBI Gene IDs and NCBI orthology mappings.

Proper citation: Orthology.eg.db (RRID:SCR_024740) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/ExperimentHub.html

Software R package provides central location where curated data from experiments, publications or training courses can be accessed.

Proper citation: ExperimentHub (RRID:SCR_024820) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/cn.farms.html

Software R package for copy number variation analysis that allows analysis of the most common Affymetrix (250K-SNP6.0) array types and supports high-performance computing using snow and ff.

Proper citation: cn.FARMS (RRID:SCR_000289) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/CorMut.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Software package for computing correlated mutations based on selection pressure. Three methods are provided for detecting correlated mutations, including conditional selection pressure, mutual information and Jaccard index. The computation consists of two steps: First, the positive selection sites are detected; second, the mutation correlations are computed among the positive selection sites. Note that the first step is optional. Meanwhile, CorMut facilitates the comparison of the correlated mutations between two conditions by the means of correlated mutation network.

Proper citation: CorMut (RRID:SCR_000053) Copy   

•   Source: SciCrunch Registry

https://rdrr.io/bioc/spotSegmentation/

Model-based software package for processing microarray images so as to estimate foreground and background intensities. The method starts with a very simple but effective automatic gridding method, and then proceeds in two steps. The first step applies model-based clustering to the distribution of pixel intensities, using the Bayesian Information Criterion (BIC) to choose the number of groups up to a maximum of three. The second step is spatial, finding the large spatially connected components in each cluster of pixels. The method thus combines the strengths of the histogram-based and spatial approaches. It deals effectively with inner holes in spots and with artifacts. It also provides a formal inferential basis for deciding when the spot is blank, namely when the BIC favors one group over two or three.

Proper citation: spotSegmentation (RRID:SCR_001298) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/BAC.html

R software package that uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments.

Proper citation: BAC (RRID:SCR_001067) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/data/annotation/html/targetscan.Hs.eg.db.html

R software that predicts biological targets of miRNAs by searching for the presence of conserved 8mer and 7mer sites that match the seed region of each miRNA.

Proper citation: targetscan.Hs.eg.db (RRID:SCR_001068) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/globaltest.html

A software package that tests groups of covariates (or features) for association with a response variable. The package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.

Proper citation: globaltest (RRID:SCR_001256) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.12/bioc/html/rGADEM.html

R package with tools for de novo motif discovery in large-scale genomic sequence data.

Proper citation: rGADEM (RRID:SCR_001091) Copy   

•   Source: SciCrunch Registry

http://crcview.hegroup.org/

Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.

Proper citation: CRCView (RRID:SCR_007092) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/ReadqPCR.html

A software package that provides functions to read raw RT-qPCR data of different platforms.

Proper citation: ReadqPCR (RRID:SCR_000030) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/topGO.html

Software package which provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.

Proper citation: topGO (RRID:SCR_014798) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/KEGGgraph/

Software R package interface between KEGG pathway and graph object as well as collection of tools to analyze, dissect and visualize these graphs.

Proper citation: KEGGgraph (RRID:SCR_023788) Copy   

•   Source: SciCrunch Registry