Evidence map›Paper›PMID 34429855›Full record

ArticleComputational and structural biotechnology journal2021

Fast mutual exclusivity algorithm nominates potential synthetic lethal gene pairs through brute force matrix product computations.

Tarcisio Fedrizzi, Yari Ciani, Francesca Lorenzin, Thomas Cantore, Paola Gasperini, Francesca Demichelis

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Tarcisio FedrizziDepartment of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy.
Yari CianiDepartment of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy.
Francesca LorenzinDepartment of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy.
Thomas CantoreDepartment of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy.
Paola GasperiniDepartment of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy.
Francesca DemichelisDepartment of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy.

Funding

Weill Cornell Medicine (WCM) SPORE in Prostate CancerP50CA211024 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI LODA, MASSIMO · 2017 to 2021
$10.9M
European Research Council 648670NCI NIH HHS P50 CA211024
6 · The paper itself

Abstract

Mutual Exclusivity analysis of genomic aberrations contributes to the exploration of potential synthetic lethal (SL) relationships thus guiding the nomination of specific cancer cells vulnerabilities. When multiple classes of genomic aberrations and large cohorts of patients are interrogated, exhaustive genome-wide analyses are not computationally feasible with commonly used approaches. Here we present Fast Mutual Exclusivity (FaME), an algorithm based on matrix multiplication that employs a logarithm-based implementation of the Fisher's exact test to achieve fast computation of genome-wide mutual exclusivity tests; we show that brute force testing for mutual exclusivity of hundreds of millions of aberrations combinations can be performed in few minutes. We applied FaME to allele-specific data from whole exome experiments of 27 TCGA studies cohorts, detecting both mutual exclusivity of point mutations, as well as allele-specific copy number signals that span sets of contiguous cytobands. We next focused on a case study involving the loss of tumor suppressors and druggable genes while exploiting an integrated analysis of both public cell lines loss of function screens data and patients' transcriptomic profiles. FaME algorithm implementation as well as allele-specific analysis output are publicly available at https://github.com/demichelislab/FaME.

Indexed as

Cancer genomicsComputational genomicsMutual exclusivitySynthetic lethality

Identifiers

PMID34429855
PMCPMC8369001

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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.