Evidence map›Paper›PMID 38586040›Full record

ArticlebioRxiv : the preprint server for biology2024

Transcript-specific enrichment enables profiling rare cell states via scRNA-seq.

Tsion Abay, Robert R Stickels, Meril T Takizawa, Benan N Nalbant, Yu-Hsin Hsieh, Sidney Hwang, Catherine Snopkowski, Kenny Kwok Hei Yu, Zaki Abou-Mrad, Viviane Tabar and 4 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 2 institutions in 2 countries.

Tsion AbayGladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.ORCID 0009-0009-0024-2732
Robert R StickelsGladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.ORCID 0000-0003-4326-4084
Meril T TakizawaSingle-cell Analytics Innovation Lab, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Benan N NalbantComputational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Yu-Hsin HsiehComputational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Sidney HwangGladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.
Catherine SnopkowskiSingle-cell Analytics Innovation Lab, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Kenny Kwok Hei YuDepartment of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Zaki Abou-MradDepartment of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Viviane TabarDepartment of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Leif S LudwigBerlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
Ronan ChalignéSingle-cell Analytics Innovation Lab, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0003-4332-3291
Ansuman T SatpathyGladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.ORCID 0000-0002-5167-537X
Caleb A LareauComputational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0003-4179-4807
Memorial Sloan Kettering Cancer Center · USGladstone Institutes · US

Funding

Single-cell Mapping Center for Human Regulatory Elements and Gene ActivityUM1HG012076 · NHGRI · STANFORD UNIVERSITY · PI Michael Ryan Corces, Ansuman Satpathy · 2021 to 2026
$13.8M
Charting somatic evolution via single-cell multiomicsR00HG012579 · NHGRI · SLOAN-KETTERING INST CAN RESEARCH · PI LAREAU, CALEB ANDREW · 2023 to 2025
$747k
NHGRI NIH HHS R00 HG012579NHGRI NIH HHS UM1 HG012076
6 · The paper itself

Abstract

Single-cell genomics technologies have accelerated our understanding of cell-state heterogeneity in diverse contexts. Although single-cell RNA sequencing (scRNA-seq) identifies many rare populations of interest that express specific marker transcript combinations, traditional flow sorting limits our ability to enrich these populations for further profiling, including requiring cell surface markers with high-fidelity antibodies. Additionally, many single-cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address these limitations, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables scRNA-seq profiling of subpopulations from complex cellular mixtures defined by the presence or absence of specific RNA transcripts. Across immune populations (

Identifiers

PMID38586040
PMCPMC10996707
OpenAlexW4393276473

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.