Evidence map›Paper›PMID 35255944›Full record

ArticleGenome biology2022

TraSig: inferring cell-cell interactions from pseudotime ordering of scRNA-Seq data.

Dongshunyi Li, Jeremy J Velazquez, Jun Ding, Joshua Hislop, Mo R Ebrahimkhani, Ziv Bar-Joseph

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

18 citing papers in PubMed, 19 citations in OpenAlex.

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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

6 authors at 3 institutions in 2 countries.

Dongshunyi Li *Computational Biology Department, School of Computer Science, Carnegie Mellon Universit, Pittsburgh, 15213, PA, USA.
Jeremy J Velazquez *Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, 15213, PA, USA.
Jun DingMeakins-Christie Laboratories, Department of Medicine, McGill University Health Centre, Montreal, H4A 3J1, Quebec, Canada.
Joshua HislopDepartment of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, 15213, PA, USA.
Mo R EbrahimkhaniDepartment of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, 15213, PA, USA. mo.ebr@pitt.edu.
Ziv Bar-JosephComputational Biology Department, School of Computer Science, Carnegie Mellon Universit, Pittsburgh, 15213, PA, USA.
University of Pittsburgh · USCarnegie Mellon University · USMcGill University Health Centre · CA

Funding

Pittsburgh Liver Research CenterP30DK120531 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CLAUDETTE Marie ST CROIX · 2019 to 2026
$10.9M
Cellular Approaches to Tissue Engineering/RegenerationT32EB001026 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DUNCAN, ANDREW W, MONGA, SATDARSHAN SINGH · 2003 to 2024
$5.5M
Comprehensive, Flexible and FAIR Tools for the HuBMAP HIVEOT2OD026682 · OD · CARNEGIE-MELLON UNIVERSITY · PI PATEN, BENEDICT, RUFFALO, MATTHEW · 2018 to 2021
$3.4M
Recreating Human Developmental Hematopoietic Niches for Ex Vivo Biomanufacturing of Blood Stem CellsR01HL141805 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Mo Reza Ebrahimkhani · 2019 to 2026
$2.6M
Integration of systems and synthetic biology to advance development of human tissues ex vivoR01EB028532 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI EBRAHIMKHANI, MO REZA · 2019 to 2022
$1.7M
Reconstructing regulatory networks from time series single cell dataR01GM122096 · NIGMS · CARNEGIE-MELLON UNIVERSITY · PI BAR-JOSEPH, ZIV · 2017 to 2020
$1.4M
BETA-CATENIN AS A THERAPEUTIC TARGET IN HEPATOCELLULAR CANCERR01CA124414 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MONGA, SATDARSHAN SINGH · 2007 to 2011
$1.3M
NCI NIH HHS R01 CA124414NHLBI NIH HHS R01 HL141805NIBIB NIH HHS R01 EB028532NIBIB NIH HHS T32 EB001026NIDDK NIH HHS P30 DK120531NIGMS NIH HHS R01 GM122096NIH HHS OT2 OD026682
6 · The paper itself

Abstract

A major advantage of single cell RNA-sequencing (scRNA-Seq) data is the ability to reconstruct continuous ordering and trajectories for cells. Here we present TraSig, a computational method for improving the inference of cell-cell interactions in scRNA-Seq studies that utilizes the dynamic information to identify significant ligand-receptor pairs with similar trajectories, which in turn are used to score interacting cell clusters. We applied TraSig to several scRNA-Seq datasets and obtained unique predictions that improve upon those identified by prior methods. Functional experiments validate the ability of TraSig to identify novel signaling interactions that impact vascular development in liver organoids.Software https://github.com/doraadong/TraSig .

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisCell CommunicationSequence Analysis, RNASoftwareCell-cell interactionsDevelopmentGene expression

Identifiers

PMID35255944
PMCPMC8900372
OpenAlexW4221044879

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.