Data used by the barcode package for microarrays of type hgu133plus2.

Affymetrix huex10 annotation data (chip huex10sttranscriptcluster) assembled using data from public repositories.

Affymetrix Affymetrix Hu6800 Array annotation data (chip hu6800) assembled using data from public repositories.

This package provides functions for plotting heatmaps of genome-wide data across genomic intervals, such as ChIP-seq signals at peaks or across promoters. Many functions are also provided for investigating sequence features.

This package provides a package containing an environment representing the HG-U133A_tag.CDF file.

Agilent "Human Genome, Whole" annotation data (chip hgug4112a) assembled using data from public repositories.

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

The HiCPotts package provides a comprehensive Bayesian framework for analyzing Hi-C interaction data, integrating both spatial and genomic biases within a probabilistic modeling framework. At its core, HiCPotts leverages the Potts model (Wu, 1982)—a well-established graphical model—to capture and quantify spatial dependencies across interaction loci arranged on a genomic lattice. By treating each interaction as a spatially correlated random variable, the Potts model enables robust segmentation of the genomic landscape into meaningful components, such as noise, true signals, and false signals. To model the influence of various genomic biases, HiCPotts employs a regression-based approach incorporating multiple covariates: Genomic distance (D): The distance between interacting loci, recognized as a fundamental driver of contact frequency. GC-content (GC): The local GC composition around the interacting loci, which can influence chromatin structure and interaction patterns. Transposable elements (TEs): The presence and abundance of repetitive elements that may shape contact probability through chromatin organization. Accessibility score (Acc): A measure of chromatin openness, informing how accessible certain genomic regions are to interaction. By embedding these covariates into a hierarchical mixture model, HiCPotts characterizes each interaction’s probability of belonging to one of several latent components. The model parameters, including regression coefficients, zero-inflation parameters (for ZIP/ZINB distributions), and dispersion terms (for NB/ZINB distributions), are inferred via a MCMC sampler. This algorithm draws samples from the joint posterior distribution, allowing for flexible posterior inference on model parameters and hidden states. From these posterior samples, HiCPotts computes posterior means of regression parameters and other quantities of interest. These posterior estimates are then used to calculate the posterior probabilities that assign each interaction to a specific component. The resulting classification sheds light on the underlying structure: distinguishing genuine high-confidence interactions (signal) from background noise and potential false signals, while simultaneously quantifying the impact of genomic biases on observed interaction frequencies. In summary, HiCPotts seamlessly integrates spatial modeling, bias correction, and probabilistic classification into a unified Bayesian inference framework. It provides rich posterior summaries and interpretable, model-based assignments of interaction states, enabling researchers to better understand the interplay between genomic organization, biases, and spatial correlation in Hi-C data.

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 Hu35KsubA\_probe\_tab.

This package provides a package containing an environment representing the Hu35KsubB.CDF file.

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

This package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions.

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\_U95A\_probe\_tab.

This package provides a package containing an environment representing the HT_MG-430_PM.cdf file.

This package was created by frmaTools version 1.13.0.

Agilent Human 1A (V2) annotation data (chip hgug4110b) assembled using data from public repositories.

This package provides a package containing an environment representing the Hu6800subD.CDF file.

RNG_MRC Human Pangenomic 25k Set annotation data (chip hs25kresogen) assembled using data from public repositories.

Systematic 3D interaction calls and differential analysis for Hi-C and HiChIP. The HiC-DC+ (Hi-C/HiChIP direct caller plus) package enables principled statistical analysis of Hi-C and HiChIP data sets – including calling significant interactions within a single experiment and performing differential analysis between conditions given replicate experiments – to facilitate global integrative studies. HiC-DC+ estimates significant interactions in a Hi-C or HiChIP experiment directly from the raw contact matrix for each chromosome up to a specified genomic distance, binned by uniform genomic intervals or restriction enzyme fragments, by training a background model to account for random polymer ligation and systematic sources of read count variation.

Agilent Human 1 cDNA Microarray Kit annotation data (chip hgug4100a) assembled using data from public repositories.

This package was created by frmaTools version 1.19.3 and hgu133ahsentrezgcdf version 19.0.0.

Agilent Chips that use Agilent design number 026652 annotation data (chip HsAgilentDesign026652) assembled using data from public repositories.

This package provides a package containing an environment representing the HT_Rat-Focus.cdf file.

Codelink UniSet Human 20k I Bioarray annotation data (chip h20kcod) assembled using data from public repositories.