HiBED
This is the released version of HiBED; for the devel version, see HiBED.
HiBED
Bioconductor version: 3.23 · Package version: 1.10.0
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.
Author: Ze Zhang [cre, aut] 
, Lucas A. Salas [aut]
Maintainer: Ze Zhang <ze.zhang.gr at dartmouth.edu>
Citation
From within R, enter citation("HiBED"):
Ze Zhang, Lucas A. Salas. HiBED: HiBED. doi:10.18129/B9.bioc.HiBED, R package version 1.10.0, https://bioconductor.org/packages/HiBED.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("HiBED")For older versions of R, please refer to the appropriate Bioconductor release.
Details
| Version | 1.10.0 |
| License | GPL-3 |
| URL | https://github.com/SalasLab/HiBED |
| Bug Reports | https://github.com/SalasLab/HiBED/issues. |
| Last updated | 2026-05-05 |
| In Bioconductor since | BioC 3.18 (R-4.3) (2 years) |
| Downloads rank | 402 of 434 |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | ExperimentData, Genome, Homo_sapiens_Data, MethylationArrayData, MicroarrayData, PackageTypeData, Tissue |
| Package Short Url | https://bioconductor.org/packages/HiBED/ |
Documentation
| Reference Manual |
Download
Follow the installation instructions to use this package in your R session.
| Source package | HiBED_1.10.0.tar.gz |
| Source Repository | git clone https://git.bioconductor.org/packages/HiBED |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/HiBED |
| Package Downloads Report | Download Stats |
Dependencies
Depends: R (>= 3.5.0)
Imports: dplyr, FlowSorted.Blood.EPIC, tibble, FlowSorted.DLPFC.450k, minfi, utils, AnnotationHub, SummarizedExperiment
Suggests: knitr, rmarkdown, testthat, IlluminaHumanMethylation450kmanifest