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CREsted
PublicCREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.pycisTopic
Publicsingle_cell_toolkit
Publicscatac_fragment_tools
PublicTools for working with scATAC-seq fragment filesPUMATAC_tutorial
PublicSpatialNF
PublicPUMATAC
Publicpycistarget
PublicDeepBrain
PublicDeepBrain: a collection of vertebrate sequence-based enhancer models aimed at understanding brain cell type enhancer code across and within speciespySCENIC
PublicpySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.SCENIC
Publicarboreto
PublicA scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.cisTopic
Publicctxcore
PublicAUCell
PublicRcisTarget
Publicshap
PublicscATAC-seq_benchmark
Publicscenicplus_analyses
Publicspatial_fly_website
PublicMendelCraft
PublicBravo_et_al_Liver
PublicLoomXpy
PublicFlyBrain_website
Public