theislab / vevo_Tahoe_100m_analysisLinks
☆34Updated 7 months ago
Alternatives and similar repositories for vevo_Tahoe_100m_analysis
Users that are interested in vevo_Tahoe_100m_analysis are comparing it to the libraries listed below
Sorting:
- Fast Gene Set Enrichment Analysis (GSEA) implementation of the prerank algorithm. Use Loess interpolation of bimodal ES distribution for …☆57Updated 7 months ago
- Decima is a Python library to train sequence models on single-cell RNA-seq data.☆58Updated this week
- scooby: Modeling multi-modal genomic profiles from DNA sequence at single-cell resolution.☆49Updated last month
- Multi-modal single cell analysis pipelines☆61Updated 2 weeks ago
- Comparing performance across many methodological dimensions among tools that predict RNA after TF knockdowns and overexpression.☆21Updated 3 months ago
- Using BCR and expression for sequence embedding☆25Updated 2 weeks ago
- ☆61Updated last year
- TCRconv is a deep learning model for predicting recognition between T cell receptors and epitopes. It uses protBERT embeddings for the TC…☆25Updated 3 years ago
- ☆44Updated last year
- Pipeline to run scE2G☆32Updated 2 months ago
- ☆26Updated 7 months ago
- Netbooks is a JupyterHub catalog of use cases in gene regulatory network inference using netZoo methods..☆45Updated 2 months ago
- High-definition modeling of chromatin + transcriptomics data☆26Updated 8 months ago
- A single-cell and spatial RNA-seq database for Alzheimer’s Disease☆26Updated last year
- Molecular interactions inference from single-cell multi-omics data☆30Updated 2 months ago
- ☆19Updated last year
- Universal Single-Cell Genomics Preprocessing package☆45Updated last week
- CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for desi…☆53Updated this week
- Material for the "Advanced topics in single-cell analysis" course (2022 edition)☆17Updated 3 years ago
- Dataloader for applying sequence models to personalized genomics☆27Updated this week
- scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics☆56Updated last year
- ☆35Updated 9 months ago
- A Python implementation of the LEMUR algorithm for analyzing multi-condition single-cell RNA-seq data.☆27Updated 11 months ago
- metadata and data from the database☆41Updated 5 years ago
- ☆96Updated last month
- Nextflow pipeline to re-process all public single-cell RNA-seq data☆30Updated 5 months ago
- CAusal Reasoning for Network Identification with integer VALue programming in R☆61Updated 2 years ago
- ☆69Updated 2 months ago
- A single-cell analysis toolkit to jointly analyze samples from distinct conditions☆34Updated 8 months ago
- Information-based dimensionality reduction☆29Updated last year