Evidence map›Paper›PMID 33894945›Full record

ArticleCell systems2021

SIGNAL: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from genome-scale assays.

Samuel Katz, Jian Song, Kyle P Webb, Nicolas W Lounsbury, Clare E Bryant, Iain D C Fraser

Abstract read
In one paragraph

Article in Cell systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. GPR15-guided CD8Nature · 2026
    Article
  2. Article
  3. Vps18 contributes to phagosome membrane integrity inbioRxiv : the preprint server for biology · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Multi-omics ofFrontiers in cardiovascular medicine · 2022
    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

6 authors.

Samuel KatzNIAID, National Institutes of Health, Laboratory of Immune System Biology, Bethesda, MD 20892, USA; University of Cambridge, Department of Veterinary Medicine, Cambridge, UK.
Jian SongNIAID, National Institutes of Health, Laboratory of Immune System Biology, Bethesda, MD 20892, USA.
Kyle P WebbNIAID, National Institutes of Health, Laboratory of Immune System Biology, Bethesda, MD 20892, USA.
Nicolas W LounsburyNIAID, National Institutes of Health, Laboratory of Immune System Biology, Bethesda, MD 20892, USA.
Clare E BryantUniversity of Cambridge, Department of Veterinary Medicine, Cambridge, UK.
Iain D C FraserNIAID, National Institutes of Health, Laboratory of Immune System Biology, Bethesda, MD 20892, USA. Electronic address: fraseri@nih.gov.

Funding

RNAi Screening in Hematopoietic CellsZIAAI001106 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI FRASER, IAIN · 2009 to 2025
$12.4M
Analysis of Innate Immune Signaling NetworksZIAAI001107 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI FRASER, IAIN · 2009 to 2025
$11.9M
Wellcome Trust 108045Wellcome Trust 108045/Z/15/Z
6 · The paper itself

Abstract

Hit selection from high-throughput assays remains a critical bottleneck in realizing the potential of omic-scale studies in biology. Widely used methods such as setting of cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions offer divergent solutions yet are associated with critical analytical trade-offs. The specific limitations of these individual approaches and the lack of a systematic way by which to integrate their rankings have contributed to limited overlap in the reported results from comparable genome-wide studies and costly inefficiencies in secondary validation efforts. Using comparative analysis of parallel independent studies as a benchmark, we characterize the specific complementary contributions of each approach and demonstrate an optimal framework to integrate these methods. We describe selection by iterative pathway group and network analysis looping (SIGNAL), an integrated, iterative approach that uses both pathway and network methods to optimize gene prioritization. SIGNAL is accessible as a rapid user-friendly web-based application (https://signal.niaid.nih.gov). A record of this paper's transparent peer review is included in the Supplemental information.

Indexed as

GenomicsHigh-Throughput Screening AssaysHumansInternetbioinformaticsenrichmentgenome-wide studiesgenomicshigh-throughput hit selectionnetwork analysispathway analysisprioritizationsoftware

Identifiers

PMID33894945
PMCPMC7613048

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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.