Affymetrix Affymetrix HT_HG-U133A Array annotation data (chip hthgu133a) assembled using data from public repositories.

Affymetrix Affymetrix HG_U95E Array annotation data (chip hgu95e) 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 provides a function that reads in the GEO accession code of a gene expression dataset, retrieves its data from GEO, and checks if data of healthy controls are present in the dataset. It returns true if healthy controls data are found, and false otherwise. GEO: Gene Expression Omnibus. ID: identifier code. The GEO datasets are downloaded from the URL <https://ftp.ncbi.nlm.nih.gov/geo/series/>.

This package provides a package containing an environment representing the HG-U133_Plus_2.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 HT\_HG-U133A\_probe\_tab.

This package provides a package containing an environment representing the HG_U95E.CDF file.

This package provides a package containing an environment representing the Hu6800subA.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 HG-U133A\_tag\_probe\_tab.

Codelink UniSet Human I Bioarray (~10 000 human genes) annotation data (chip h10kcod) assembled using data from public repositories.

This package contains the data used in the vignettes and examples of the h5vc package.

Affymetrix Affymetrix Hu35KsubC Array annotation data (chip hu35ksubc) assembled using data from public repositories.

HGC (short for Hierarchical Graph-based Clustering) is an R package for conducting hierarchical clustering on large-scale single-cell RNA-seq (scRNA-seq) data. The key idea is to construct a dendrogram of cells on their shared nearest neighbor (SNN) graph. HGC provides functions for building graphs and for conducting hierarchical clustering on the graph. The users with old R version could visit https://github.com/XuegongLab/HGC/tree/HGC4oldRVersion to get HGC package built for R 3.6.

Gene-level count matrix data for bulk RNA-seq dataset with many replicates. The data are provided as easy to use SummarizedExperiment objects. The source data that is made accessible through this package comes from https://github.com/bartongroup/profDGE48.

Hierarchical deconvolution for extensive cell type resolution in the human brain using DNA methylation. The HiBED deconvolution estimates proportions up to 7 cell types (GABAergic neurons, glutamatergic neurons, astrocytes, microglial cells, oligodendrocytes, endothelial cells, and stromal cells) in bulk brain tissues.

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.

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.

In epigenome-wide association studies, the measured signals for each sample are a mixture of methylation profiles from different cell types. The current approaches to the association detection only claim whether a cytosine-phosphate-guanine (CpG) site is associated with the phenotype or not, but they cannot determine the cell type in which the risk-CpG site is affected by the phenotype. We propose a solid statistical method, HIgh REsolution (HIRE), which not only substantially improves the power of association detection at the aggregated level as compared to the existing methods but also enables the detection of risk-CpG sites for individual cell types. The "HIREewas" R package is to implement HIRE model in R.

This package provides tools to perform hierarchical inference for one or multiple studies / data sets based on high-dimensional multivariate (generalised) linear models. A possible application is to perform hierarchical inference for GWA studies to find significant groups or single SNPs (if the signal is strong) in a data-driven and automated procedure. The method is based on an efficient hierarchical multiple testing correction and controls the FWER. The functions can easily be run in parallel.

Utility package to facilitate integration and analysis of EBI HoloFood data in R. This package streamlines access to the resource, allowing for direct loading of data into formats optimized for downstream analytics.

This package provides a package to generate high-resolution Venn and Upset plots for genomic interaction data from HiC, ChIA-PET, HiChIP, PLAC-Seq, Hi-TrAC, HiCAR and etc. The package generates plots specifically crafted to eliminate the deceptive visual representation caused by the counts method.

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.

An interactive tool to visualize long vectors of integer data by means of Hilbert curves.

Codelink Human Whole Genome Bioarray (~55 000 human genes) annotation data (chip hwgcod) assembled using data from public repositories.