This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Hu35KsubB\_probe\_tab.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was HG-U95D\_probe\_tab.

This package allows a direct access to the dataset generated by the Human Cell Atlas project for further processing in R and Bioconductor, in the comfortable format of SingleCellExperiment objects (available in other formats here: http://preview.data.humancellatlas.org/).

Example HapMap data from Illumina 370k BeadChips.

This package contains functions to interact with tally data from NGS experiments that is stored in HDF5 files.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was HG-U133A\_probe\_tab.

Affymetrix hta20 annotation data (chip hta20probeset) assembled using data from public repositories.

Affymetrix huex10 annotation data (chip huex10stprobeset) assembled using data from public repositories.

The iterative Bayesian Model Averaging (BMA) algorithm for survival analysis is a variable selection method for applying survival analysis to microarray data.

iSEEtree is an extension of iSEE for the TreeSummarizedExperiment data container. It provides interactive panel designs to explore hierarchical datasets, such as the microbiome and cell lines.

Integrative copy number variation (CNV) detection from multiple platform and experimental design.

The iNETgrate package provides functions to build a correlation network in which nodes are genes. DNA methylation and gene expression data are integrated to define the connections between genes. This network is used to identify modules (clusters) of genes. The biological information in each of the resulting modules is represented by an eigengene. These biological signatures can be used as features e.g., for classification of patients into risk categories. The resulting biological signatures are very robust and give a holistic view of the underlying molecular changes.

This R package supports the handling and analysis of imaging mass cytometry and other highly multiplexed imaging data. The main functionality includes reading in single-cell data after image segmentation and measurement, data formatting to perform channel spillover correction and a number of spatial analysis approaches. First, cell-cell interactions are detected via spatial graph construction; these graphs can be visualized with cells representing nodes and interactions representing edges. Furthermore, per cell, its direct neighbours are summarized to allow spatial clustering. Per image/grouping level, interactions between types of cells are counted, averaged and compared against random permutations. In that way, types of cells that interact more (attraction) or less (avoidance) frequently than expected by chance are detected.

Manifest for Illumina's 27k array data.

An R package for integrated differential expression and differential network analysis based on omic data for cancer biomarker discovery. Both correlation and partial correlation can be used to generate differential network to aid the traditional differential expression analysis to identify changes between biomolecules on both their expression and pairwise association levels. A detailed description of the methodology has been published in Methods journal (PMID: 27592383). An interactive visualization feature allows for the exploration and selection of candidate biomarkers.

Utility functions for working with CONCH data, listing remote files. One function assigns HoverNet nuclei to ProvGigaPath tiles with a scale factor to align coordinates. Provides internal utility functions for imageFeatureTCGA and most functions are not meant for end users.

Illumina HumanWGDASLv4 annotation data (chip illuminaHumanWGDASLv4) assembled using data from public repositories.

This package performs Intron-Exon Retention analysis on RNA-seq data (.bam files).

Illumina MouseWG6v1p1 annotation data (chip illuminaMousev1p1) assembled using data from public repositories.

Iteratively Adjusted Surrogate Variable Analysis (IA-SVA) is a statistical framework to uncover hidden sources of variation even when these sources are correlated. IA-SVA provides a flexible methodology to i) identify a hidden factor for unwanted heterogeneity while adjusting for all known factors; ii) test the significance of the putative hidden factor for explaining the unmodeled variation in the data; and iii), if significant, use the estimated factor as an additional known factor in the next iteration to uncover further hidden factors.

Reconstructing Interlog Protein Network (IPN) integrated from several Protein protein Interaction Networks (PPINs). Using this package, overlaying different PPINs to mine conserved common networks between diverse species will be applicable.

This package provides a manifest package for use with Illumina's MSA methylation arrays, compatible with minfi.

This package contains diverse functionality to extend the usage of the iSEE package, including additional classes for the panels or modes facilitating the analysis of differential expression results. This package does not perform differential expression. Instead, it provides methods to embed precomputed differential expression results in a SummarizedExperiment object, in a manner that is compatible with interactive visualisation in iSEE applications.

Illumina MouseWG6v2 annotation data (chip illuminaMousev2) assembled using data from public repositories.