Evidence map›Paper›PMID 28045996›Full record

ArticlePloS one2017

Validation of Immune Cell Modules in Multicellular Transcriptomic Data.

Gabriele Pollara, Matthew J Murray, James M Heather, Rachel Byng-Maddick, Naomi Guppy, Matthew Ellis, Carolin T Turner, Benjamin M Chain, Mahdad Noursadeghi

Abstract read
In one paragraph

Article in PloS one, 2017. 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
–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

18 citing papers in PubMed.

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  9. Vitamin DImmunotherapy advances · 2021
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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

9 authors.

Gabriele PollaraDivision of Infection & Immunity, University College London, London, United Kingdom.ORCID http://orcid.org/0000-0001-5772-0322
Matthew J MurrayDivision of Infection & Immunity, University College London, London, United Kingdom.
James M HeatherDivision of Infection & Immunity, University College London, London, United Kingdom.
Rachel Byng-MaddickDivision of Infection & Immunity, University College London, London, United Kingdom.
Naomi GuppyUCL Advanced Diagnostics, University College London, London, United Kingdom.
Matthew EllisDepartment of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, United Kingdom.
Carolin T TurnerDivision of Infection & Immunity, University College London, London, United Kingdom.
Benjamin M ChainDivision of Infection & Immunity, University College London, London, United Kingdom.
Mahdad NoursadeghiDivision of Infection & Immunity, University College London, London, United Kingdom.

Funding

Arthritis Research UK 20131Cancer Research UK 20256Medical Research Council MR/M003833/1Wellcome Trust
6 · The paper itself

Abstract

Numerous gene signatures, or modules have been described to evaluate the immune cell composition in transcriptomes of multicellular tissue samples. However, significant diversity in module gene content for specific cell types is associated with heterogeneity in their performance. In order to rank modules that best reflect their purported association, we have generated the modular discrimination index (MDI) score that assesses expression of each module in the target cell type relative to other cells. We demonstrate that MDI scores predict modules that best reflect independently validated differences in cellular composition, and correlate with the covariance between cell numbers and module expression in human blood and tissue samples. Our analyses demonstrate that MDI scores provide an ordinal summary statistic that reliably ranks the accuracy of gene expression modules for deconvolution of cell type abundance in transcriptional data.

Indexed as

Cell CountGene Expression ProfilingGene Expression RegulationHumansLeukocytesLymph NodesReproducibility of ResultsSkinTranscriptome

Identifiers

PMID28045996
PMCPMC5207692

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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.