ArticleNature methods2021
Fast searches of large collections of single-cell data using scfind.
Article in Nature methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- HuBMAP Data Portal: a resource for multimodal spatial and single-cell data of healthy human tissues.ArXiv · 2026Article
- SpatialQuery: scalable discovery and molecular characterization of multicellular motifs from spatial omics data.bioRxiv : the preprint server for biology · 2026Article
- Mining alternative splicing patterns in scRNA-seq data using scASfind.Genome biology · 2024Article
- Matching queried single-cell open-chromatin profiles to large pools of single-cell transcriptomes and epigenomes for reference supported analysis.Genome research · 2023Article
- Nonnegative spatial factorization applied to spatial genomics.Nature methods · 2023Article
- scHumanNet: a single-cell network analysis platform for the study of cell-type specificity of disease genes.Nucleic acids research · 2023Article
- Production of human entorhinal stellate cell-like cells by forward programming shows an important role of Foxp1 in reprogramming.Frontiers in cell and developmental biology · 2022Article
- Diffusion enables integration of heterogeneous data and user-driven learning in a desktop knowledge-base.PLoS computational biology · 2021Article
- Fast searches of large collections of single-cell data using scfind.Nature methods · 2021Article
- Comparison of visualization tools for single-cell RNAseq data.NAR genomics and bioinformatics · 2020Article
- Integrated Transcriptome and Network Analysis Reveals Spatiotemporal Dynamics of Calvarial Suturogenesis.Cell reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Single-cell technologies have made it possible to profile millions of cells, but for these resources to be useful they must be easy to query and access. To facilitate interactive and intuitive access to single-cell data we have developed scfind, a single-cell analysis tool that facilitates fast search of biologically or clinically relevant marker genes in cell atlases. Using transcriptome data from six mouse cell atlases, we show how scfind can be used to evaluate marker genes, perform in silico gating, and identify both cell-type-specific and housekeeping genes. Moreover, we have developed a subquery optimization routine to ensure that long and complex queries return meaningful results. To make scfind more user friendly, we use indices of PubMed abstracts and techniques from natural language processing to allow for arbitrary queries. Finally, we show how scfind can be used for multi-omics analyses by combining single-cell ATAC-seq data with transcriptome data.
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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.