Hierarchical, iterative clustering for analysis of transcriptomics data in R
-
Updated
Aug 20, 2025 - HTML
Hierarchical, iterative clustering for analysis of transcriptomics data in R
Open-ST: profile and analyze tissue transcriptomes in 3D with high resolution in your lab
Materials used during #NGSchool2017
Isocomp provides tools to compare any number of transcriptome assemblies (GTF + fasta) from long read RNAseq
Lightweight single-html-file-based Genome Segments playground for Visualize genome features cluster(gene arrow map or other features), add synteny among genome fragments or add crosslink among features, add short(PE/MP)/long reads(pacbio or nanopore) mapping or snpindel in vcf(not support complex sv yet), support all CIGAR of sam alignment, dire…
An R package to plot interactive three-way differential expression analysis
The blog of tidyomics
Digital Expression Explorer 2 (DEE2): a repository of uniformly processed RNA-seq data
ImaGene: A multi-omic ML/AI software with guided operational reports and supporting files
A comprehensive analysis tool for Ribo-seq and small RNA-seq data
Deep-neural protein translation
spatialDLPFC project involving Visium (n = 30), Visium SPG (n = 4) and snRNA-seq (n = 19) samples
Single cell RNA-seq analysis for transcriptomic type characterization
Reproducibility of "Alternative start and termination sites of transcription drive most transcript isoform differences across human tissues."
feseR: Combining feature selection methods for analyzing omics data
Differential gene expression data from the human central nervous system across Alzheimer’s disease, Lewy body diseases, and ALS-FTD.
Multi-omics module that includes RNAseq, Epigenetics, and integrated multi-omics analyses developed as part of the NIGMS Sandbox project
scBubbletree: quantitative tool for visual exploration of scRNA-seq data
Review on 'Reconciling Multiple Connectivity Scores for Drug Repurposing.'
OmicsSuite website for releasing new version.
Add a description, image, and links to the transcriptomics topic page so that developers can more easily learn about it.
To associate your repository with the transcriptomics topic, visit your repo's landing page and select "manage topics."