preciseTADhub
This is the released version of preciseTADhub; for the devel version, see preciseTADhub.
Pre-trained random forest models obtained using preciseTAD
Bioconductor version: Release (3.23)
An experimentdata package to supplement the preciseTAD package containing pre-trained models and the variable importances of each genomic annotation used to build the model parsed into list objects and available in ExperimentHub. In total, preciseTADhub provides access to n=84 random forest classification models optimized to predict TAD/chromatin loop boundary regions and stored as .RDS files. The value, n, comes from the fact that we considered l=2 cell lines {GM12878, K562}, g=2 ground truth boundaries {Arrowhead, Peakachu}, and c=21 autosomal chromosomes {CHR1, CHR2, ..., CHR22} (omitting CHR9). Furthermore, each object is itself a two-item list containing: (1) the model object, and (2) the variable importances for CTCF, RAD21, SMC3, and ZNF143 used to predict boundary regions. Each model is trained via a "holdout" strategy, in which data from chromosomes {CHR1, CHR2, ..., CHRi-1, CHRi+1, ..., CHR22} were used to build the model and the ith chromosome was reserved for testing. See https://doi.org/10.1101/2020.09.03.282186 for more detail on the model building strategy.
Author: Spiro Stilianoudakis [aut], Mikhail Dozmorov [aut, cre]
Maintainer: Mikhail Dozmorov <mikhail.dozmorov at gmail.com>
citation("preciseTADhub")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("preciseTADhub")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("preciseTADhub")| preciseTADhub | HTML | R Script |
| Reference Manual | ||
| LICENSE | Text |
Details
| biocViews | ExperimentData, ExperimentHub, Genome, PackageTypeData |
| Version | 1.20.0 |
| License | MIT + file LICENSE |
| Depends | R (>= 4.1) |
| Imports | ExperimentHub |
| System Requirements | |
| URL | https://github.com/dozmorovlab/preciseTADhub |
| Bug Reports | https://github.com/dozmorovlab/preciseTADhub/issues |
See More
| Suggests | knitr, rmarkdown, markdown, BiocStyle, preciseTAD |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | preciseTADhub_1.20.0.tar.gz |
| Windows Binary (x86_64) | |
| macOS Binary (big-sur-x86_64) | |
| macOS Binary (sonoma-arm64) | |
| Source Repository | git clone https://git.bioconductor.org/packages/preciseTADhub |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/preciseTADhub |
| Package Short Url | https://bioconductor.org/packages/preciseTADhub/ |
| Package Downloads Report | Download Stats |