daehwankimlab.github.io - Resource for downloading all the HISAT2 related files
Please cite:
Kim, D., Paggi, J.M., Park, C. et al. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol 37, 907–915...
github.com - Peregrine is a fast genome assembler for accurate long reads (length > 10kb, accuracy > 99%). It can assemble a human genome from 30x reads within 20 cpu hours from reads to polished consensus. It uses Sparse HIereachical MimiMizER (SHIMMER)...
www.science.org - Telomere-to-telomere consortium
We have sequenced the CHM13hTERT human cell line with a number of technologies. Human genomic DNA was extracted from the cultured cell line. As the DNA is native, modified bases will be preserved. The data includes...
github.com - The Genome Context Viewer (GCV) is a web-app that visualizes genomic context data provided by third party services. Specifically, it uses functional annotations as a unit of search and comparison. By adopting a common set of annotations, data-store...
https://js.cgview.ca/ - CGView.js is a Circular Genome Viewing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program CGView.
CGView.js is the genome viewer of Proksee, an expert system for genome...
lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing...
mira-assembler.sourceforge.net - MIRA is a multi-pass DNA sequence data assembler/mapper for whole genome and EST/RNASeq projects. MIRA assembles/maps reads gained by
electrophoresis sequencing (aka Sanger sequencing)
454 pyro-sequencing (GS20, FLX or Titanium)
Ion...
github.com - Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format. Different from mainstream...
github.com - ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set.
Detail paper...