Additional file 1: Figure S1. of A 26-hour system of highly sensitive whole genome sequencing for emergency management of genetic diseases

Screen-shots demonstrating the functionality of SSAGA. A. The clinical feature entry page. Synonyms for each feature are entered in the top left box. Upon entry, a list of matching HPO terms is displayed. The appropriate HPO term is selected and added to the patient’s feature list in the box on the right. This is performed for each clinical feature. In this case, patient CMH672ref, the patient had 11 clinical features that included neonatal seizures and a characteristic facies. B. Upon clicking the ‘Get Diagnosis’ button, the list of all matching diseases is generated. In this case, the differential diagnosis had 1,136 rows, representing 597 genes, of which 222 matched two or more clinical features. (PDF 240 kb

La Petite presse : journal quotidien... / [rédacteur en chef : Balathier Bragelonne]

19 septembre 18791879/09/19 (A13,N4882)

precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regions

The precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new machine-learning approaches combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants

PrecisionFDA Truth Challenge V2: Calling variants from short and long reads in difficult-to-map regions

The precisionFDA Truth Challenge V2 aimed to assess the state of the art of variant calling in challenging genomic regions. Starting with FASTQs, 20 challenge participants applied their variant-calling pipelines and submitted 64 variant call sets for one or more sequencing technologies (Illumina, PacBio HiFi, and Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with updated Genome in a Bottle benchmark sets and genome stratifications. Challenge submissions included numerous innovative methods, with graph-based and machine learning methods scoring best for short-read and long-read datasets, respectively. With machine learning approaches, combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants