Development of an Expert Knowledge-Based Genomic Variant Prioritisation Platform
Egileak: Grégory Maclair Martinez. Iride Vidales, Concha
Data: 01.01.2022
Studies in Health Technology and Informatics
Abstract
Considering the growing interest towards next generation sequencing (NGS) and data analysis, and the substantial challenges associated to fully exploiting these technologies and data without the proper experience, an expert knowledge-based user-friendly analytical tool was developed to allow non-bioinformatics experts to process NGS genomic data, automatically prioritise genomic variants and make their own annotations. This tool was developed using a user-centred methodology, where an iterative process was followed until a useful product was developed. This tool allows the users to set-up the pre-processing pipeline, filter the obtained data, annotate it using external and local databases (DBs) and help on deciding which variants are more relevant for each study, taking advantage of its customised expert-based scoring system. The end users involved in the project concluded that CRIBOMICS was easy to learn, use and interact with, reducing the analysis time and possible errors of variant prioritisation for genetic diagnosis. © 2022 The authors and IOS Press.
BIB_text
title = {Development of an Expert Knowledge-Based Genomic Variant Prioritisation Platform},
journal = {Studies in Health Technology and Informatics},
pages = {45-48},
volume = {Vol. 289},
keywds = {
genetic variants prioritisation; Genomics; standalone tool; user-centred design
}
abstract = {
Considering the growing interest towards next generation sequencing (NGS) and data analysis, and the substantial challenges associated to fully exploiting these technologies and data without the proper experience, an expert knowledge-based user-friendly analytical tool was developed to allow non-bioinformatics experts to process NGS genomic data, automatically prioritise genomic variants and make their own annotations. This tool was developed using a user-centred methodology, where an iterative process was followed until a useful product was developed. This tool allows the users to set-up the pre-processing pipeline, filter the obtained data, annotate it using external and local databases (DBs) and help on deciding which variants are more relevant for each study, taking advantage of its customised expert-based scoring system. The end users involved in the project concluded that CRIBOMICS was easy to learn, use and interact with, reducing the analysis time and possible errors of variant prioritisation for genetic diagnosis. © 2022 The authors and IOS Press.
}
doi = {10.3233/SHTI210855},
date = {2022-01-01},
}
