Evidence map›Paper›PMID 25534632›Full record

ArticleBMC genomics2014

Simultaneous analysis of large-scale RNAi screens for pathogen entry.

Pauli Rämö, Anna Drewek, Cécile Arrieumerlou, Niko Beerenwinkel, Houchaima Ben-Tekaya, Bettina Cardel, Alain Casanova, Raquel Conde-Alvarez, Pascale Cossart, Gábor Csúcs and 32 more

Abstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Artificial Intelligence Methods in Infection Biology Research.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Review
  18. Viral entry pathways: the example of common cold viruses.Wiener medizinische Wochenschrift (1946) · 2016
    Review
  19. Article
  20. 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

42 authors.

Pauli Rämö
Anna Drewek
Cécile Arrieumerlou
Niko Beerenwinkel
Houchaima Ben-Tekaya
Bettina Cardel
Alain Casanova
Raquel Conde-Alvarez
Pascale Cossart
Gábor Csúcs
Simone Eicher
Mario Emmenlauer
Urs Greber
Wolf-Dietrich Hardt
Ari Helenius
Christoph Kasper
Andreas Kaufmann
Saskia Kreibich
Andreas Kühbacher
Peter Kunszt
Shyan Huey Low
Jason Mercer
Daria Mudrak
Simone Muntwiler
Lucas Pelkmans
Javier Pizarro-Cerdá
Michael Podvinec
Eva Pujadas
Bernd Rinn
Vincent Rouilly
Fabian Schmich
Juliane Siebourg-Polster
Berend Snijder
Michael Stebler
Gabriel Studer
Ewa Szczurek
Matthias Truttmann
Christian von Mering
Andreas Vonderheit
Artur Yakimovich
Peter Bühlmann
Christoph DehioFocal Area Infection Biology, Biozentrum, University of Basel, Klingelberstrasse 70, CH-4056 Basel, Switzerland. christoph.dehio@unibas.ch.

Funding

European Research Council 233348
6 · The paper itself

Abstract

backgroundLarge-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries.

resultsWe show that PMM gains statistical power for hit detection due to parallel screening. PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators. By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied.

conclusionsOur results show parallel RNAi screening can improve the results of individual screens. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.

Indexed as

RNA InterferenceCell LineGene LibraryGenomicsHigh-Throughput Screening AssaysHost-Pathogen InteractionsHumansReproducibility of ResultsRNA, Small InterferingROC CurveRNA, Small Interfering

Identifiers

PMID25534632
PMCPMC4326433

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.