Evidence map›Paper›PMID 36824707›Full record

ArticlebioRxiv : the preprint server for biology2023

Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA).

Courtney Schiebout, Hannah E Lust, Yina H Huang, H Robert Frost

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Courtney SchieboutDepartment of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Hanover, NH USA.
Hannah E LustMDI Biological Laboratory, Bar Harbor, ME USA.
Yina H HuangDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, NH USA.
H Robert FrostDepartment of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Hanover, NH USA.

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI Li Song · 2019 to 2026
$27.2M
Gene set analysis of single cell genomicsR35GM146586 · NIGMS · DARTMOUTH COLLEGE · PI Hildreth Frost · 2022 to 2026
$2.0M
Cancer-specific gene set testingR21CA253408 · NCI · DARTMOUTH COLLEGE · PI FROST, HILDRETH · 2020 to 2020
$451k
NCI NIH HHS P30 CA023108NCI NIH HHS R21 CA253408NIGMS NIH HHS P20 GM130454NIGMS NIH HHS R35 GM146586Wellcome Trust
6 · The paper itself

Abstract

Motivation: Doublets are usually considered an unwanted artifact of single-cell RNA-sequencing (scRNA-seq) and are only identified in datasets for the sake of removal. However, if cells have a juxtacrine attachment to one another in situ and maintain this association through an scRNA-seq processing pipeline that only partially dissociates the tissue, these doublets can provide meaningful biological information regarding the interactions and cell processes occurring in the analyzed tissue. This is especially true for cases such as the immune compartment of the tumor microenvironment, where the frequency and type of immune cell juxtacrine interactions can be a prognostic indicator. Results: We developed Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA) as a pipeline for identifying and analyzing biological doublets in scRNA-seq data. CIcADA identifies putative doublets using multi-label cell type scores and characterizes interaction dynamics through a comparison against synthetic doublets of the same cell type composition. In performing CIcADA on several scRNA-seq tumor datasets, we found that the identified doublets were consistently upregulating expression of immune response genes. Contact: Courtney.T.Schiebout.GR@Dartmouth.edu , Hildreth.R.Frost@Dartmouth.edu.

Identifiers

PMID36824707
PMCPMC9949061

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Registered trials

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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.