github.com - evolverSimControl (eSC) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (Newick format). In addition to simply running evolver, eSC also automatically creates statistical summaries of the simulation...
In graph theory, a string graph is an intersection graph of curves in the plane; each curve is called a "string". String graphs were first proposed by E. W. Myers in a 2005 publication.
mummer4.github.io - MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing...
github.com - AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.
Using AlignGraph
AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa...
www.fishbrowser.org - P_RNA_scaffolder, a fast and accurate tool using paired-end RNA-sequencing reads to scaffold genomes. This tool aims to improve the completeness of both protein-coding and non-coding genes. After this tool was applied to scaffolding human contigs,...
github.com - LR_Gapcloser is a gap closing tool using long reads from studied species. The long reads could be downloaed from public read archive database (for instance, NCBI SRA database ) or be your own data. Then they are fragmented and aligned to scaffolds...
eugi.bi.up.ac.za - swgis v2.0 is the modified version of the seqword genomic island sniffer. this version is specifically optimized for predicting genomic islands in eukaryotic genomes. swgis v2.0 was tested on several eukaryotic species of different lineages....
sourceforge.net - GenomeView is a genome browser and annotation editor that displays reference sequence, annotation, multiple alignments, short read alignments and graphs. Most major data formats are supported. Local and internet files can be loaded.This project has...
To decide which strategy should be our “preferred” genome assembly approach based on data rather than my gut-feeling about the “best assembly” I decided to do some testing with a known “true” reference E Coli K12 MG1655