Sample dataset obtained from http://www.hapmap.org.

This package provides a package containing an environment representing the Hu35KsubA.CDF file.

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 Hu35KsubC\_probe\_tab.

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

This package provides a package containing an environment representing the Hu6800.CDF file.

Affymetrix Human Genome 219 Plate annotation data (chip hgu219) assembled using data from public repositories.

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

Sample dataset obtained from http://www.hapmap.org.

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 HT\_MG-430B\_probe\_tab.

Annotation data file for hgu2beta7 assembled using data from public data repositories.

This package provides access to the scRNA-seq, scATAC-seq, multiome, CITE-seq and spatial transcriptomics (Visium) data generated by the tonsil cell atlas in the context of the Human Cell Atlas (HCA). The data is provided via the Bioconductor project in the form of SingleCellExperiments. Additionally, information on the whole compendium of identified cell types is provided in form of a glossary.

This package provides a package for detecting differential methylation. It exploits a Bayesian hidden Markov model that incorporates location dependence among genomic loci, unlike most existing methods that assume independence among observations. Bayesian priors are applied to permit information sharing across an entire chromosome for improved power of detection. The direct output of our software package is the best sequence of methylation states, eliminating the use of a subjective, and most of the time an arbitrary, threshold of p-value for determining significance. At last, our methodology does not require replication in either or both of the two comparison groups.

Harman is a PCA and constrained optimisation based technique that maximises the removal of batch effects from datasets, with the constraint that the probability of overcorrection (i.e. removing genuine biological signal along with batch noise) is kept to a fraction which is set by the end-user.

This package provides a package containing an environment representing the HG_U95A.CDF file.

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

Data used by the barcode package for microarrays of type hgu133a.

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 HT\_HG-U133A\_probe\_tab.

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

HubPub provides users with functionality to help with the Bioconductor Hub structures. The package provides the ability to create a skeleton of a Hub style package that the user can then populate with the necessary information. There are also functions to help add resources to the Hub package metadata files as well as publish data to the Bioconductor S3 bucket.

Affymetrix Affymetrix HT_HG-U133_Plus_B Array annotation data (chip hthgu133plusb) assembled using data from public repositories.

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 HT\_HG-U133B\_probe\_tab.

This package was automatically created by package AnnotationDbi version 1.11.8. The exon-level probeset genome location was retrieved from Netaffx using AffyCompatible. The exon-level probeset genome location was retrieved from Netaffx using AffyCompatible. Genome release hg19.

Package with metadata for genotyping Illumina Omni1 Quad arrays using the crlmm package.