This software is meant to be used for classification of images of cell-based assays for neuronal surface autoantibody detection or similar techniques. It takes imaging files as input and creates a composite score from these, that for example can be used to classify samples as negative or positive for a certain antibody-specificity. The reason for its name is that I during its creation have thought about the individual picture as an archielago where we with different filters control the water level as well as ground characteristica, thereby finding islands of interest.

Implementation of the Interval-Wise Testing (IWT) for omics data. This inferential procedure tests for differences in "Omics" data between two groups of genomic regions (or between a group of genomic regions and a reference center of symmetry), and does not require fixing location and scale at the outset.

An annotation package for Illumina's EPIC methylation arrays.

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.

Illumina HumanWG6v2 annotation data (chip illuminaHumanv2) assembled using data from public repositories.

Illumina HumanHT12v3 annotation data (chip illuminaHumanv3) assembled using data from public repositories.

integrated Bayesian Modeling of eQTL data.

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.

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

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.

The imcdatasets package provides access to publicly available IMC datasets. IMC is a technology that enables measurement of > 40 proteins from tissue sections. The generated images can be segmented to extract single cell data. Datasets typically consist of three elements: a SingleCellExperiment object containing single cell data, a CytoImageList object containing multichannel images and a CytoImageList object containing the cell masks that were used to extract the single cell data from the images.

It fits correlation motif model to multiple RNAseq or ChIPseq studies to improve detection of allele-specific events and describe correlation patterns across studies.

IsoCorrectoR performs the correction of mass spectrometry data from stable isotope labeling/tracing metabolomics experiments with regard to natural isotope abundance and tracer impurity. Data from both MS and MS/MS measurements can be corrected (with any tracer isotope: 13C, 15N, 18O...), as well as ultra-high resolution MS data from multiple-tracer experiments (e.g. 13C and 15N used simultaneously). See the Bioconductor package IsoCorrectoRGUI for a graphical user interface to IsoCorrectoR. NOTE: With R version 4.0.0, writing correction results to Excel files may currently not work on Windows. However, writing results to csv works as before.

Characterization of miRNAs and isomiRs, clustering and differential expression.

An annotation package for Illumina's MSA methylation arrays.

Illumina HumanHT12WGDASLv3 annotation data (chip illuminaHumanWGDASLv3) assembled using data from public repositories.

This package provides a tool to measure reproducibility between genomic experiments that produce two-dimensional peaks (interactions between peaks), such as ChIA-PET, HiChIP, and HiC. idr2d is an extension of the original idr package, which is intended for (one-dimensional) ChIP-seq peaks.

ISLET is a method to conduct signal deconvolution for general -omics data. It can estimate the individual-specific and cell-type-specific reference panels, when there are multiple samples observed from each subject. It takes the input of the observed mixture data (feature by sample matrix), and the cell type mixture proportions (sample by cell type matrix), and the sample-to-subject information. It can solve for the reference panel on the individual-basis and conduct test to identify cell-type-specific differential expression (csDE) genes. It also improves estimated cell type mixture proportions by integrating personalized reference panels.

Identification of genetic variants affecting alternative splicing.

The package is focused on the detection of correlation between expressed genes and selected epigenomic signals (i.e. enhancers obtained from ChIP-seq data) either within topologically associated domains (TADs) or between chromatin contact loop anchors. Various parameters can be controlled to investigate the influence of external factors and visualization plots are available for each analysis step.

All alleles from the IPD IMGT/HLA <https://www.ebi.ac.uk/ipd/imgt/hla/> and IPD KIR <https://www.ebi.ac.uk/ipd/kir/> database for Homo sapiens. Reference: Robinson J, Maccari G, Marsh SGE, Walter L, Blokhuis J, Bimber B, Parham P, De Groot NG, Bontrop RE, Guethlein LA, and Hammond JA KIR Nomenclature in non-human species Immunogenetics (2018), in preparation.

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

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.

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