BOL

github.com - Software package for signal-level analysis of Oxford Nanopore sequencing data. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome...

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 - The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by Oxford Nanopore flow cells. Computational methods used by the Shasta assembler include: Using...

github.com - genome simulation across a population with zeta-distributed allele frequency, snps, insertions, deletions, and multi-nucleotide polymorphisms More at https://github.com/ekg/mutatrix ./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta

Genetic variants discovery tool

www.nature.com - The human genome is arguably the most complete mammalian reference assembly yet more than 160 euchromatic gaps remain and aspects of its structural variation remain poorly understood ten years after its completion. The results in this paper...

www.nature.com - Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs. https://www.nature.com/articles/nm.3975

github.com - This tool is used to merge structural variants (SVs) across samples. Each sample has a number of SV calls, consisting of position information (chromosome, start, end, length), type and strand information, and a number of other values. Jasmine...

github.com - Automatic Filtering, Trimming, Error Removing and Quality Control for fastq dataAfterQC can simply go through all fastq files in a folder and then output three folders: good, bad and QC folders, which contains good...

github.com - Other tools focus on getting data out of the fastq or fast5 files, which is slow and computationally intensive. The benefit of this approach is that it works on a single, small, .txt summary file. So it's a lot quicker than most other things out...