Dataset Information

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization.

ABSTRACT:

Background

Whole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts.

Methods

We developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient's standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA).

Results

ClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes.

Conclusions

ClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses.

SUBMITTER: Schluter A

PROVIDER: S-EPMC10486091 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization.

Schlüter Agatha A Vélez-Santamaría Valentina V Verdura Edgard E Rodríguez-Palmero Agustí A Ruiz Montserrat M Fourcade Stéphane S Planas-Serra Laura L Launay Nathalie N Guilera Cristina C Martínez Juan José JJ Homedes-Pedret Christian C Albertí-Aguiló M Antonia MA Zulaika Miren M Martí Itxaso I Troncoso Mónica M Tomás-Vila Miguel M Bullich Gemma G García-Pérez M Asunción MA Sobrido-Gómez María-Jesús MJ López-Laso Eduardo E Fons Carme C Del Toro Mireia M Macaya Alfons A Beltran Sergi S Gutiérrez-Solana Luis G LG Pérez-Jurado Luis A LA Aguilera-Albesa Sergio S de Munain Adolfo López AL Casasnovas Carlos C Pujol Aurora A

Genome medicine 20230907 1

<h4>Background</h4>Whole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical da ...[more]

PMID: 37679823

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Project description:BackgroundLatest Next Generation Sequencing technologies opened the way to a novel era of genomic studies, allowing to gain novel insights into multifactorial pathologies as cancer. In particular gene fusion detection and comprehension have been deeply enhanced by these methods. However, state of the art algorithms for gene fusion identification are still challenging. Indeed, they identify huge amounts of poorly overlapping candidates and all the reported fusions should be considered for in lab validation clearly overwhelming wet lab capabilities.ResultsIn this work we propose a novel methodological approach and tool named FuGePrior for the prioritization of gene fusions from paired-end RNA-Seq data. The proposed pipeline combines state of the art tools for chimeric transcript discovery and prioritization, a series of filtering and processing steps designed by considering modern literature on gene fusions and an analysis on functional reliability of gene fusion structure.ConclusionsFuGePrior performance has been assessed on two publicly available paired-end RNA-Seq datasets: The first by Edgren and colleagues includes four breast cancer cell lines and a normal breast sample, whereas the second by Ren and colleagues comprises fourteen primary prostate cancer samples and their paired normal counterparts. FuGePrior results accounted for a reduction in the number of fusions output of chimeric transcript discovery tools that ranges from 65 to 75% depending on the considered breast cancer cell line and from 37 to 65% according to the prostate cancer sample under examination. Furthermore, since both datasets come with a partial validation we were able to assess the performance of FuGePrior in correctly prioritizing real gene fusions. Specifically, 25 out of 26 validated fusions in breast cancer dataset have been correctly labelled as reliable and biologically significant. Similarly, 2 out of 5 validated fusions in prostate dataset have been recognized as priority by FuGePrior tool.

Dataset Information

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization.

Background

Methods

Results

Conclusions

Publications

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization.

Similar Datasets

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