ArticleMethods in molecular biology (Clifton, N.J.)2021
Inference of Gene Regulatory Network from Single-Cell Transcriptomic Data Using pySCENIC.
Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 74 papers.
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74 citing papers in PubMed.
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- Single-cell profiling of DNA methylation in autism spectrum disorder prefrontal cortex reveals distinct regulatory and aging signatures.Cell genomics · 2026Article
- Single-Cell Pan-Cancer Atlas Reveals GPR171 as a Candidate Marker of CD8International journal of molecular sciences · 2026Article
- A large-scale single-nucleus resource reveals a cardiomyocyte-like fibroblast and stage-specific remodeling across cardiomyopathies.BMC medicine · 2026Article
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- Disparate periphery and lung immune microenvironments induced monocyte-macrophage activation as a key factor in anti-synthetase syndrome-associated interstitial lung disease.Respiratory research · 2026Article
- Single-nucleus transcriptomics illuminates sex differences during murine Escherichia coli pyelonephritis.Communications biology · 2026Article
- ENS lineage potential is not intrinsically regionalized but is modulated by PTPRZ1 signaling.bioRxiv : the preprint server for biology · 2026Article
- Identification of Skin Multicellular Reprogramming Factors as Potential Treatment for Nonhealing Diabetic Foot Ulcers.Advances in wound care · 2026Article
- Single-Cell Profiling Across Immune Tissues and Organs Reveals Immunosenescence Signatures in Male Rhesus Monkeys.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Modeling mitochondrial inheritance enables high-precision single-cell lineage tracing in humans.bioRxiv : the preprint server for biology · 2026Article
- High resolution spatial transcriptomic and proteomic profiling of early primate gastrulationbioRxiv : the preprint server for biology · 2026Article
- PU.1 inhibition sensitizes stem-monocytic AML to BCL2 blockade.bioRxiv : the preprint server for biology · 2026Article
- Data driven network inference and longitudinal transcriptomics unveil dynamic regulation in Chronic Lymphocytic Leukaemia models.NPJ systems biology and applications · 2026Article
14 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
With the advent of recent next-generation sequencing (NGS) technologies in genomics, transcriptomics, and epigenomics, profiling single-cell sequencing became possible. The single-cell RNA sequencing (scRNA-seq) is widely used to characterize diverse cell populations and ascertain cell type-specific regulatory mechanisms. The gene regulatory network (GRN) mainly consists of genes and their regulators-transcription factors (TF). Here, we describe the lightning-fast Python implementation of the SCENIC (Single-Cell reEgulatory Network Inference and Clustering) pipeline called pySCENIC. Using single-cell RNA-seq data, it maps TFs onto gene regulatory networks and integrates various cell types to infer cell-specific GRNs. There are two fast and efficient GRN inference algorithms, GRNBoost2 and GENIE3, optionally available with pySCENIC. The pipeline has three steps: (1) identification of potential TF targets based on co-expression; (2) TF-motif enrichment analysis to identify the direct targets (regulons); and (3) scoring the activity of regulons (or other gene sets) on single cell types.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.