Subsets of Promoter Capture Hi-C data conveniently packaged for Chicago users. Data includes interactions detected for chromosomes 20 and 21 in GM12878 cells and for chromosomes 18 and 19 in mESC.

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

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

Platform Design Info for Affymetrix MoGene-1_0-st-v1.

Phantasus is a web-application for visual and interactive gene expression analysis. Phantasus is based on Morpheus – a web-based software for heatmap visualisation and analysis, which was integrated with an R environment via OpenCPU API. Aside from basic visualization and filtering methods, R-based methods such as k-means clustering, principal component analysis or differential expression analysis with limma package are supported.

Platform Design Info for Affymetrix miRNA-3_0.

PhIPData defines an S4 class for phage-immunoprecipitation sequencing (PhIP-seq) experiments. Buliding upon the RangedSummarizedExperiment class, PhIPData enables users to coordinate metadata with experimental data in analyses. Additionally, PhIPData provides specialized methods to subset and identify beads-only samples, subset objects using virus aliases, and use existing peptide libraries to populate object parameters.

PathNet uses topological information present in pathways and differential expression levels of genes (obtained from microarray experiment) to identify pathways that are 1) significantly enriched and 2) associated with each other in the context of differential expression. The algorithm is described in: 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.

Platform Design Info for Affymetrix GenomeWideSNP_6.

Platform Design Info for Affymetrix Clariom_S_Mouse_HT.

This is a package that includes pre-processing and quality control functions that can remove margin events, compensate and transform the data and that will use PeacoQCSignalStability for quality control. This last function will first detect peaks in each channel of the flowframe. It will remove anomalies based on the IsolationTree function and the MAD outlier detection method. This package can be used for both flow- and mass cytometry data.

Platform Design Info for NimbleGen 2006-07-18_mm8_refseq_promoter.

The package contains the function for filtering genes by the proportion of variation accounted for by the first principal component (PVAC).

Platform Design Info for The Manufacturer's Name HG-U219.

An automated pipeline for the detection, integration and reporting of predefined features across a large number of mass spectrometry data files. It enables the real time annotation of multiple compounds in a single file, or the parallel annotation of multiple compounds in multiple files. A graphical user interface as well as command line functions will assist in assessing the quality of annotation and update fitting parameters until a satisfactory result is obtained.

This package provide simulation based methods for evaluating the statistical power in differential expression analysis from RNA-seq data.

Most analyses of Affymetrix GeneChip data (including tranditional 3 arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3 arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.

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.

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

Runs PANDA, an algorithm for discovering novel network structure by combining information from multiple complementary data sources.

Platform Design Info for The Manufacturer's Name HT_HG-U133A.

Platform Design Info for The Manufacturer's Name Zebrafish.

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

This package provides S4 classes and methods for inferring functional gene networks with edges encoding posterior beliefs of gene association types and nodes encoding perturbation effects.