BenchHub
Comprehensive Collection of Curated Benchmarking Datasets and their Evaluation
Bioconductor version: 3.24 · Package version: 0.99.15
The trio is the combination of a data set, a metric and supporting evidence which provides some best case scenario, if not the ground truth itself. BenchHub has data downloaders for FigShare, G.E.O., and ExperimentHub. Caching is used to avoid lengthy downloads after the first time a data set is accessed. The user may also specify their own data set and supporting evidence. The Benchmark Insights module provides functionality for comparing and contrasting the performance of alternative algorithms.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("BenchHub") Details
| Maintainer | SOMS Maintainer <maths.bioconductor@sydney.edu.au> |
| Author | Cabiria Liang [aut], Sanghyun Kim [aut], Nick Robertson [aut], Marni Torkel [aut], Yue Cao [aut] (ORCID: <https://orcid.org/0000-0002-2356-4031>), Dario Strbenac [aut], Jean Yang [aut], SOMS Maintainer [aut, cre] |
| License | MIT + file LICENSE |
| URL | https://sydneybiox.github.io/BenchHub/ |
| Bug Reports | https://github.com/SydneyBioX/BenchHub/issues |
| Downloads rank | 61 |
| Source branch | devel |
| biocViews | DataImport, DataRepresentation, Infrastructure, Software, Visualization, WorkflowStep |
Documentation
- 1 Introduction to the Trio Class
- 2 Evaluation using Trio
- 3 Introduction of BenchmarkInsights class
- 4 Preparing and Submitting a Trio
- 5 BenchmarkStudy
Download
Follow the installation instructions to use this package in your R session.
| Source package | BenchHub_0.99.15.tar.gz |
| Windows binary (x86_64) | BenchHub_0.99.15.zip |
| macOS binary (arm64) | BenchHub_0.99.15.tgz |
| macOS binary (x86_64) | BenchHub_0.99.15.tgz |
Dependencies
Depends: R (>= 4.5.0)
Imports: cli, fs, glue, R6, rlang, httr2, stringr, purrr, dplyr, reshape2, utils, curl, googlesheets4, survAUC, Hmisc, ggrepel, ggsci, ggcorrplot, broom, dotwhisker, splitTools, magrittr, withr, ggplot2, data.table, jsonlite
Suggests: anndata, readr, GEOquery, ExperimentHub, zen4R, knitr, ks, rmarkdown, SingleCellExperiment, SummarizedExperiment, survival, cvTools, funkyheatmap, testthat (>= 3.0.0), clusterProfiler, DOSE, DO.db, EnsDb.Hsapiens.v86, BiocStyle, tidyverse, glmnet, scran, scuttle, edgeR