rnalib: a python-based transcriptomics library
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Updated
Jun 6, 2024 - Jupyter Notebook
rnalib: a python-based transcriptomics library
Annotated data.
From geospatial to spatial -omics
National Microbiome Data Collaborative (NMDC) unified data model
scBubbletree: quantitative tool for visual exploration of scRNA-seq data
This repository gives an overview of my teaching activities. Links to slides and data sets are included. Feel free to re-use my content.
Characterize gene dynamics over trajectories using GLMs, GEEs, & GLMMs.
Single-cell analysis in Python. Scales to >1M cells.
Currently working on multi-omics data analysis, featuring tools for data integration, processing, and visualization, with a focus on R and Python.
A Python package to search, retrieve, and prepare gene expression data from Gene Expression Omnibus and Genomic Data Commons.
An ontology of cell types
COSMOS (Causal Oriented Search of Multi-Omic Space) is a method that integrates phosphoproteomics, transcriptomics, and metabolomics data sets.
A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.
An interactive explorer for single-cell transcriptomics data
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
spatially aware scalable and accurate tool for spot deconvolution and clustering in spatial transcriptomics
Snakemake pipeline for use in computing cluster to pull RNA-seq fastq reads from GEO, trim, run quality checks and align. Output interfaces with MADRID
Hierarchical, iterative clustering for analysis of transcriptomics data in R
Metabolic state prediction at single-cell resolution is a project developed as a Bachelor's Thesis (TFG), to recover metabolic states from single-cell expression data.
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