github.com - ClinCNV detects CNVs in germline and somatic context in NGS data (targeted and whole-genome). We work in cohorts, so it makes sense to try ClinCNV if you have more than 10 samples (recommended amount - 40 since we estimate variances from...
https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html
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Degree in bioinformatics, biostatistics, or equivalent
Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance...
genohub.com - The right sequencing instrument for your study depends on your project goal. Setting aside turnaround time and price, it essentially comes down to the numbers of reads and read length you need for your experiment. Below, we've described and compared...
Consider a scenario in which a patient's genome has been sequenced. Among billions of DNA bases, a structural alteration may explain the patient's disease. Multiple advanced algorithms analyze the data, yet only one detects the variant, while the...
FYI, I've found it useful to use MUMmer to extract the specific changes that Racon makes, so I can evaluate them individually:
minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta...
gwct.github.io - Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site...
github.com - jackalope simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina and Pacific Biosciences (PacBio) platforms. It can either read reference genomes from FASTA files or simulate new ones. Genomic variants...
github.com - Welcome to kevlar, software for predicting de novo genetic variants without mapping reads to a reference genome! kevlar's k-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs),...