Dex-Benchmark: datasets and code to evaluate algorithms for transcriptomics data analysis.

ABSTRACT: Many tools and algorithms are available for analyzing transcriptomics data. These include algorithms for performing sequence alignment, data normalization and imputation, clustering, identifying differentially expressed genes, and performing gene set enrichment analysis. To make the best choice about which tools to use, objective benchmarks can be developed to compare the quality of different algorithms to extract biological knowledge maximally and accurately from these data. The Dexamethasone Benchmark (Dex-Benchmark) resource aims to fill this need by providing the community with datasets and code templates for benchmarking different gene expression analysis tools and algorithms. The resource provides access to a collection of curated RNA-seq, L1000, and ChIP-seq data from dexamethasone

SUBMITTER: Xie Z 

PROVIDER: S-EPMC10638921 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature