github.com - LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs).
LAMSA takes takes the...
github.com - HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig...
www.healthcare.uiowa.edu - Getting Started
These simple steps will help you integrate LSC into your transcriptomics analysis pipeline.
Read the LSC_requirements for running LSC.
Download and set-up the LSC package.
Follow the tutorial to see how...
github.com - LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation...
github.com - new de novo assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE...
bioinformaticsdotca.github.io - In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will...
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 - HECIL—Hybrid Error Correction with Iterative Learning—a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read...
chagall.med.cornell.edu - Institute of computational biomedicine, Cornell University provide an NGS workshop tutorial at http://chagall.med.cornell.edu/NGScourse/
You can also add your favourite NGS educational material, or workshop tutorial by commenting on this...