Mohammad Lotfollahi, Chelsea Bright, Ronald Skorobogat, Mohammad Moghareh Dehkordi, Xavier George, Simon Richter, Vladimir A. Shitov, Aleksandra Topalova, Helena Melcher, Noah Nussbaumer, Annika Fomm, Malte D. Luecken, Fabian J. Theis
{"title":"ArchMap is a web-based platform for reference-based analysis of single-cell datasets","authors":"Mohammad Lotfollahi, Chelsea Bright, Ronald Skorobogat, Mohammad Moghareh Dehkordi, Xavier George, Simon Richter, Vladimir A. Shitov, Aleksandra Topalova, Helena Melcher, Noah Nussbaumer, Annika Fomm, Malte D. Luecken, Fabian J. Theis","doi":"10.1038/s41588-026-02756-y","DOIUrl":null,"url":null,"abstract":"Leveraging single-cell reference atlases to analyze new data has brought about a paradigm shift in single-cell data science akin to the first reference genome in genomics. However, methods for performing this mapping require computational expertise and, oftentimes, considerable compute power, limiting access for researchers who may benefit the most. Here ArchMap, a no-code query-to-reference mapping tool, removes this barrier by providing all-in-one automated mapping, cell-type annotation and collaborative features to analyze single-cell datasets from a wide range of integrated, often published, reference atlases and allows the extension of atlases with the growing Human Cell Atlas and related efforts. This paves the way for a democratization of reference mapping capabilities. Existing software for mapping single-cell datasets onto reference atlases often requires coding expertise or a license. ArchMap is a free no-code query-to-reference mapping web tool compatible with Python-based mapping methods.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 10","pages":"2469-2473"},"PeriodicalIF":25.5000,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-026-02756-y.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature genetics","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41588-026-02756-y","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Leveraging single-cell reference atlases to analyze new data has brought about a paradigm shift in single-cell data science akin to the first reference genome in genomics. However, methods for performing this mapping require computational expertise and, oftentimes, considerable compute power, limiting access for researchers who may benefit the most. Here ArchMap, a no-code query-to-reference mapping tool, removes this barrier by providing all-in-one automated mapping, cell-type annotation and collaborative features to analyze single-cell datasets from a wide range of integrated, often published, reference atlases and allows the extension of atlases with the growing Human Cell Atlas and related efforts. This paves the way for a democratization of reference mapping capabilities. Existing software for mapping single-cell datasets onto reference atlases often requires coding expertise or a license. ArchMap is a free no-code query-to-reference mapping web tool compatible with Python-based mapping methods.
期刊介绍:
Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation.
Integrative genetic topics comprise, but are not limited to:
-Genes in the pathology of human disease
-Molecular analysis of simple and complex genetic traits
-Cancer genetics
-Agricultural genomics
-Developmental genetics
-Regulatory variation in gene expression
-Strategies and technologies for extracting function from genomic data
-Pharmacological genomics
-Genome evolution