Discover aertslab/PUMATAC Open Source project by @aertslab

SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.

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SCENIC

SCENIC+ is a python package to build gene regulatory networks (GRNs) using combined or separate single-cell gene expression (scRNA-seq) and single-cell chromatin accessibility (scATAC-seq) data.

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scenicplus

A scalable SCENIC workflow for single-cell gene regulatory network analysis

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SCENICprotocol

cisTopic: Probabilistic modelling of cis-regulatory topics from single cell epigenomics data

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cisTopic

AUCell: score single cells with gene regulatory networks

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AUCell

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SCope

Fast visualization tool for large-scale and high dimensional single-cell data

pycisTopic is a Python module to simultaneously identify cell states and cis-regulatory topics from single cell epigenomics data.

pycisTopic

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

arboreto

Create cisTarget databases

create_cisTarget_databases

R package (compatible with SCope) to create generic .loom files and extend them with other data e.g.: SCENIC regulons, Seurat clusters and markers, ...

SCopeLoomR

RcisTarget

RcisTarget: Transcription factor binding motif enrichment

GENIE3 (GEne Network Inference with Ensemble of trees) R-package

GENIE3

CREsted

ScoMAP is an R package to spatially integrate single-cell omics data into virtual cells and infer enhancer-to-gene relationships.

ScoMAP

single_cell_toolkit

Tools for correcting single cell barcodes for various scATAC-seq techniques.

Download files from and list content of NextCloud (password protected) share directly from the command line without needing a webbrowser.

nextcloud_share_url_downloader

popscle_helper_tools

Helper tools for popscle

Scalable inference of gene regulatory networks using Apache Spark and XGBoost

GRNBoost

Scala

install_aspera_connect

Install latest version of Aspera Connect and show example how to use it for downloading sequening data.

pycistarget is a python module to perform motif enrichment analysis in sets of regions with different tools and identify high confidence TF cistromes.

pycistarget

scATAC-seq_benchmark

scenicplus_analyses

singlecellRNA_melanoma_paper

LoomXpy

Python package (compatible with SCope) to create .loom files and extend them with other data e.g.: SCENIC regulons

A repository containing the analysis scripts for Nova-ST data

Nova-ST

DeepMEL

DEPRECATED | pySCENIC pipeline implemented in Nextflow using containers

scenic-nf

Nextflow

DeepBrain

DeepBrain: a collection of vertebrate sequence-based enhancer models aimed at understanding brain cell type enhancer code across and within species

PUMATAC_tutorial

Code for reproducing the figures presented in the manuscript 'Identification of genomic enhancers through spatial integration of single-cell transcriptomics and epigenomics' (Bravo et al., 2020)

Bravo_et_al_EyeAntennalDisc

The MendelCraft mod, introducing Mendelian genetics to the chickens of Minecraft!

MendelCraft

Java

scatac_fragment_tools

Tools for working with scATAC-seq fragment files

Bravo_et_al_Liver

Iterative peak filtering.

iterative_peak_filtering

A regulon consists of a transcription factor (TF) and its direct transcriptional targets, which contain common TF binding sites in their cis-regulatory control elements. The iRegulon plugin allows you to identify regulons using motif and track discovery in an existing network or in a set of co-regulated genes.

iRegulon

Java

ctxcore

Core functions for pycisTarget and the SCENIC tool suite

Calculation of regulatory impact score of a mutation.

primescore

hydrop_data_analysis

scforest: a visual overview of single cell technology

scforest

TeX

webhdf5

HDF5 library in WASM

Some scripts for ATAC-seq data analysis

ATAC-seq-analysis

Predict cis-regulatory mutations in gene regulatory networks

mucistarget

Spatial transcriptomics NextFlow pipelines

SpatialNF

Decoding gene regulation in the fly brain

fly_brain

SCopeLoomPy

A Python notebook to create .loom files and extend them with other data e.g.: SCENIC regulons, Seurat clusters and markers, compatible with SCope

Allele specific variant pipeline

AS_variant_pipeline

Create regulatory regions delineation

regulatory_regions_delineation

Create BCF/VCF files with all DGRP2 mutations for Drosophila melanogaster (dm6) from dm3 VCF files.

DGRP2_dm3_to_dm6

Melanoma_MPRA_paper

Melanoma MPRA paper

EnhancerAI