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A knowledge-based pipeline to increase the diagnosis rate of Rare Diseases using deep sequencing

18th national competition for scientific and technical research

Rare diseases

Senior Researcher : Carmen Ayuso García

Research Centre or Institution : Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD, UAM). CIBERER. Madrid.

Abstract

The application of the Next Generation Sequencing (NGS) techniques into the field of Rare Diseases (RD) is producing an increase in their diagnosis rate. Their special features together with a continuous fall in their costs have precipitated their implementation in clinical settings involved in genetic diagnosis. This fact has implied several challenges including the bioinformatic analysis of massive data that has to be filtered and prioritized in order to extract the relevant information to every case under study. Thus, one solution has come from some distinct commercial initiatives offering very stable products that prioritizes accuracy and easy implementations. An additional weak feature of these kind of products is the limited access to primary data that impede in many cases an optimal sharing with research groups with similar objectives.

The present project proposed an integration of clinical, research and bioinformatics efforts in order to identify those characteristics that can be improved in the analysis process to increase the diagnosis rate of RD and implement alternative solutions into a customized pipeline for reanalysis. The outcome is a bioinformatics custom pipeline that complements already implemented software that is able to contribute differentially to the diagnosis of disease like retinal dystrophies, eye developmental diseases, monogenic heart diseases and hereditary cancers. Our final product reports both Single Nucleotide Variants as well as Copy Number Variations and incorporates own annotations, such as cohort specific frequency allele counts, homozygous regions mapping or new candidate genes predictions methods. In addition, we have developed a front-end software that permits analysists to make an integral analysis of DNA sequencing experiments including filtering and prioritization of variants. The whole protocol is on use to reanalyze of samples with no conclusive diagnostic from the Genetics Department of the IIS-FJD and has proven an increase in the diagnosis capacity.

 

Scientific Production
 
Magazine Articles 17
Communications at national conferences 38
Communications at international conferences 18

 

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