The need for speed in accurate and whole genome data analysis.
The challenge: To assess sensitivity/recall, precision, computation time, and disk footprint of four bioinformatic pipelines by performed alignment and variant calling for the reference short-read WGS data of NA12878 and the Ashkenazim trio.
The outcome: Genalice Map has achieved ultra- rapid speed and superior low disk footprint with BWA/ GATK-like sensitivity, thus enabling efficient (re)analyses of ever-increasing amounts of WGS data.
Population Calling module to boost variant calling in trio-sequencing.
The challenge: In family trio-sequencing it is essential to find a perfect balance between genotyping errors and variant calling sensitivity.
The solution: Genalice Population gives you the complete flexibility to boost high quality variants in your trio-sequencing data.
Roeland Van Ham (KeyGene) talks about his experience with Genalice Map in the AgriGenomics setting.
“Through the technology implemented in Genalice Map, there are specular reductions in the footprint which is a huge problem and a huge challenge…”
Pioneering an efficient migration of 13,000 whole genomes.
The challenge: Migrating a dataset of 13,000 whole genomes focused on the identification of the genetic basis of rare diseases with emphasis on cardiovascular disorders to the latest human reference standard GRCh38.
The solution: Analysis of 13,000 whole genomes shows that GRCh38 delivers better coverage and significantly more variants without detriment to quality. Alignment and variant calling for GRCh38 was completed in 20 days using 10 compute nodes.
Variant calling quality enhancement within a large breeding population.
The challenge: The massive increase in data production in agrigenomics creates growing computational and storage challenges in a time and budget constraint environment.
The solution: By implementing Genalice Population, KeyGene was able to reduce processing times by over 100 fold, whereas former hardware requirements of a cluster >1,000 cores decreased to a single machine with 12 cores. The module further increased the accuracy and efficiency for SNP variation of a large breeding population of highly homozygous individuals, derived from complex crosses between multiple parental lines.
High quality variants from 1,000 Drosophila genomes in a day.
The challenge: Mapping and variant calling of large full genome cohorts are time consuming and leave little time to actually analyse variants.
The solution: Realise a fast data processing of more than 1,000 Drosophila genomes in a single day. The speed-up realised with Genalice Population allows scientists to mine data and find the hidden gems in the variant calls.
Interview with Hywel Williams (UCL Great Ormond Street Institute of Child Health).
“We incorporated one of the (Genalice) servers into our cluster, which allowed us to drastically reduce the sample processing time, down to an average of 20 minutes per sample, meaning we could process a full trio in just one hour. Work performed by us ‘in house’ and by others has shown that this time reduction does not come at the price of accuracy or sensitivity.”