ArticleNature methods2026
Pertpy: an end-to-end framework for perturbation analysis.
Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- Quantifying distribution shifts in single-cell data with scXMatch.Bioinformatics (Oxford, England) · 2026Article
- Review
- Benchmarking methods for inferring single-cell transcription factor activity using large-scale perturbation sequencing data.Briefings in bioinformatics · 2026Article
- Donor-specific, but not sex-specific, signatures dominate cell-type classification in lung scRNA-seq data.Biochemistry and biophysics reports · 2026Article
- Single-cell-level perturbation-induced and condition-related signal estimation with batch effect removal using NDreamer.Briefings in bioinformatics · 2026Article
- Article
- The diverse functions of viral microproteins.bioRxiv : the preprint server for biology · 2026Article
- Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells.Nature biotechnology · 2026Article
- Airway immune signatures of protection and disease progression in recent human tuberculosis household contacts.Nature immunology · 2026Article
- Developmental signaling reveals functionally enriched human-specific gene regulation in telencephalic progenitors.bioRxiv : the preprint server for biology · 2026Article
- Condition-Associated Pattern Extraction and Recovery From Multi-Condition Single-Cell RNA-seq Data With CAPER.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Single-nucleus multiomic atlas of ALS primary motor cortex nominates neuroprotective WDR49-expressing astrocytes.Research square · 2026Article
- Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Supporting-like cells constitute an alternative steroidogenic lineage conserved in amniotes.bioRxiv : the preprint server for biology · 2026Article
- scArchon: a scalable benchmarking framework for assessing single-cell perturbation models.Genome biology · 2026Article
- Transforming the cytokine literature into a resource for experimental analysis and discovery.bioRxiv : the preprint server for biology · 2026Article
- ModelingbioRxiv : the preprint server for biology · 2026Article
- Hidden immune memory niches in inflammatory skin diseases.bioRxiv : the preprint server for biology · 2026Article
- Genome-scale functional mapping of the mammalian whole brain with in vivo Perturb-seq.bioRxiv : the preprint server for biology · 2026Article
- Genome-scale mapping of variant, enhancer and gene function in primary human CD4+ T cells.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
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Authors and funding
29 authors.
Funding
Abstract
Advances in single-cell technology have enabled the measurement of cell-resolved molecular states across a variety of cell lines and tissues under a plethora of genetic, chemical, environmental or disease perturbations. Current methods focus on differential comparison or are specific to a particular task in a multi-condition setting with purely statistical perspectives. The quickly growing number, size and complexity of such studies require a scalable analysis framework that takes existing biological context into account. Here we present pertpy, a Python-based modular framework for the analysis of large-scale single-cell perturbation experiments. Pertpy provides access to harmonized perturbation datasets and metadata databases along with numerous fast and user-friendly implementations of both established and novel methods, such as automatic metadata annotation or perturbation distances, to efficiently analyze perturbation data. As part of the scverse ecosystem, pertpy interoperates with existing single-cell analysis libraries and is designed to be easily extended.
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Registered trials
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.