BOL

fsa.sourceforge.net - FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a...

github.com - Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC: Fast and accurate reference-guided scaffolding of draft genomes. bioRxiv 2019. RaGOO is a tool for coalescing genome assembly contigs into...

benjjneb.github.io - The DADA2 tutorial goes through a typical workflow for paired end Illumina Miseq data: raw amplicon sequencing data is processed into the table of exact amplicon sequence variants (ASVs) present in each sample. The DADA2...

github.com - Mash is normally distributed as a dependency-free binary for Linux or OSX (see https://github.com/marbl/Mash/releases). This source distribution is intended for other operating systems or for development. Mash requires c++11 to build, which is...

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...

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 - Kalign is a fast multiple sequence alignment program for biological sequences. Align sequences and output the alignment in MSF format: kalign -i BB11001.tfa -f msf -o out.msf Align sequences and output the alignment in clustal format: kalign...

github.com - chromeister: An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons. USAGE: -query: sequence A in fasta format -db: sequence B in fasta format -out: output matrix -kmer Integer: k>1...

github.com - Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.