The pRoloc package implements machine learning and visualisation methods for the analysis and interogation of quantitiative mass spectrometry data to reliably infer protein sub-cellular localisation.

This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12.

Platform Design Info for Affymetrix RheGene-1_0-st.

Interactions between proteins occur in many, if not most, biological processes. Most proteins perform their functions in networks associated with other proteins and other biomolecules. This fact has motivated the development of a variety of experimental methods for the identification of protein interactions. This variety has in turn ushered in the development of numerous different computational approaches for modeling and predicting protein interactions. Sometimes an experiment is aimed at identifying proteins closely related to some interesting proteins. A network based statistical learning method is used to infer the putative functions of proteins from the known functions of its neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions.

This package provides a package containing an environment representing the Pae_G1a.CDF file.

PhosR is a package for the comprenhensive analysis of phosphoproteomic data. There are two major components to PhosR: processing and downstream analysis. PhosR consists of various processing tools for phosphoproteomics data including filtering, imputation, normalisation, and functional analysis for inferring active kinases and signalling pathways.

Platform Design Info for The Manufacturer's Name HG_U95E.

Platform Design Info for Affymetrix CHOGene-2_0-st.

Platform Design Info for The Manufacturer's Name Canine.

Platform Design Info for Affymetrix ZebGene-1_1-st.

Platform Design Info for The Manufacturer's Name miRNA-1_0.

This package contains the data employed in the vignette of the PathNet package. These data belong to the following publication: PathNet: A tool for pathway analysis using topological information. Dutta B, Wallqvist A, and Reifman J., Source Code for Biology and Medicine 2012 Sep 24;7(1):10.

PAST takes GWAS output and assigns SNPs to genes, uses those genes to find pathways associated with the genes, and plots pathways based on significance. Implements methods for reading GWAS input data, finding genes associated with SNPs, calculating enrichment score and significance of pathways, and plotting pathways.

This package provides tools for large-scale protein motif analysis and visualization in R. PMScanR facilitates the identification of motifs using external tools like PROSITE's ps_scan (handling necessary file downloads and execution) and enables downstream analysis of results. Key features include parsing scan outputs, converting formats (e.g., to GFF-like structures), generating motif occurrence matrices, and creating informative visualizations such as heatmaps, sequence logos (via seqLogo/ggseqlogo). The package also offers an optional Shiny-based graphical user interface for interactive analysis, aiming to streamline the process of exploring motif patterns across multiple protein sequences.

Platform Design Info for The Manufacturer's Name Ecoli_ASv2.

Platform Design Info for The Manufacturer's Name Hu6800.

Platform Design Info for Affymetrix FinGene-1_0-st.

This package provides a set of annotation maps describing the entire Gene Ontology assembled using data from PANTHER.

Platform Design Info for Affymetrix miRNA-3_1.

Platform Design Info for The Manufacturer's Name Rhesus.

Platform Design Info for The Manufacturer's Name HT_HG-U133_Plus_PM.

Phenotypes comparison based on a pathway consensus approach. Assess the relationship between candidate genes and a set of phenotypes based on additional genes related to the candidate (e.g. Pathways or network neighbors).

This package provides a function to make gene presence/absence calls based on distance from negative strand matching probesets (NSMP) which are derived from Affymetrix annotation. PANP is applied after gene expression values are created, and therefore can be used after any preprocessing method such as MAS5 or GCRMA, or PM-only methods like RMA. NSMP sets have been established for the HGU133A and HGU133-Plus-2.0 chipsets to date.

This package provides tools to test correlation between gene expression and phenotype in a way that is efficient, structured, fast and scalable. GSEA is also provided.