Evidence map›Paper›PMID 37191796›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes.

April Sagan, Xiaojun Ma, Koushul Ramjattun, Hatice Ulku Osmanbeyoglu

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

April SaganDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Xiaojun MaDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Koushul RamjattunDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Hatice Ulku OsmanbeyogluDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA. osmanbeyogluhu@pitt.edu.
University of Pittsburgh · USUPMC Hillman Cancer Center · US

Funding

The internship in Biomedical Research, Informatics, and Computer Science (iBRIC): Biomedical Informatics and Data Science research experiences for students from Minority Serving InstitutionsT15LM007059 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRY S HOCHHEISER · 1987 to 2026
$23.9M
Computational methods for delineating cell context-specific regulatory programsR35GM146989 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Hatice Ulku Osmanbeyoglu · 2022 to 2026
$1.9M
Algorithms to link signaling pathways with transcriptional programs for precision medicineR00CA207871 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI OSMANBEYOGLU, HATICE ULKU · 2019 to 2022
$738k
NCI NIH HHS R00 CA207871NIGMS NIH HHS R35 GM146989NLM NIH HHS T15 LM007059
6 · The paper itself

Abstract

Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cell multi-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.

Indexed as

ProteomeTranscriptomeHumansLeukocytes, MononuclearProteomicsSingle-Cell AnalysisTranscription FactorsProteomeTranscription FactorsAffinity regression (AR)Antibody-derived tags (ADTs)Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)DoRothEA databaseDroplet-based scRNA-seqJupyter notebookpySPaRTAN packagePython packagescADT-seqscVerse and Scanpy ecosystemsSingle-cell Proteomic and RNA-based Transcription factor Activity Network (SPaRTAN)

Identifiers

PMID37191796
OpenAlexW4376641883

What OpenQuestion holds

Textmetadata
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.