More at http://easyfig.sourceforge.net/

Address of the bookmark: http://easyfig.sourceforge.net/

ORFfinder is a graphical analysis tool for finding open reading frames (ORFs). We’ve been working on a few updates, and we’d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.

Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)

Select one or a group of ORFs and BLAST several databases at once, and use the newly developed SmartBLAST to verify protein names. Looking for the traditional results from BLAST? They’re there too.

Publication:

• L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.

Download:

• LoRMA 0.3 source files
• README

Address of the bookmark: https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/

This tool is a standalone version of Ragout module [http://fenderglass.github./Ragout]

Address of the bookmark: https://github.com/fenderglass/maf2synteny

https://www.youtube.com/watch?v=WgufqYMHCvM

Address of the bookmark: http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html

SynVisio requires two files to run:

• The simplified gff file that was used as an input for a McScanX query.
• The collinearity file generated as an output by McScanX for the same input query.
• Optional track file in bedgraph format to annotate the generated charts.

SynVisio offers different types of visualizations such as Linear Parallel plots, Hive plots, Stacked Parallel Plots and Dot plots. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.

Address of the bookmark: https://synvisio.github.io/#/

panacus supports the following calculations:

• coverage histogram
• pangenome growth statistics
• path-/group-resolved coverage table

Address of the bookmark: https://github.com/marschall-lab/panacus

Address of the bookmark: https://github.com/pnnl/fqc

Copy & Paste this line into your terminal:

\curl -L https://install.perlbrew.pl | bash

Or, if your system does not have curl but something else:

# Linux
\wget -O - https://install.perlbrew.pl | bash

# FreeBSD
\fetch -o- https://install.perlbrew.pl | sh

If you prefer to install with cpan, there are two steps:

sudo cpan App::perlbrew
perlbrew init

If it is installed with cpan, the perlbrew executable should be installed as /usr/bin/perlbrew or /usr/local/bin/perlbrew. For all users who want to use perlbrew, a prior perlbrew init needs to be executed.

The default perlbrew root directory is ~/perl5/perlbrew, which can be changed by setting PERLBREW_ROOTenvironment variable before the installation and initialization. For more advanced installation process, please read the perlbrew document.

Address of the bookmark: https://perlbrew.pl/

Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.

PLAST stands for Parallel Local Sequence Alignment Search Tool and is was published in BMC Bioinformatics.

PLAST is a general purpose sequence comparison tool providing the following benefits:

• PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),
• Reduces the processing time of sequences comparisons while providing highest quality results,
• Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),
• Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,
• Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.

https://plast.inria.fr/

Address of the bookmark: https://plast.inria.fr/