This is an extensive tutorial to take you through the main features and gotchas of configuring GBrowse as a server. This tutorial assumes that you have successfully set up Perl, GD, BioPerl and the other GBrowse dependencies. If you haven't, please see the GBrowse HOWTO During most of the tutorial, we will be using the "in-memory" GBrowse database (no relational database required!) Later we will show how to set up a genome size database using the berkeleydb and MySQL adaptors.

More at http://elp.ucdavis.edu/tutorial/tutorial.html

Address of the bookmark: http://elp.ucdavis.edu/tutorial/tutorial.html

Address of the bookmark: http://decipher.cee.wisc.edu/Documentation.html

• velvet (velveth velvetg should be in your PATH)
• R (with Sweave)
• pdflatex (usually part of TeTeX)
• ggplot2 (from R prompt type install.packages("ggplot2","proto","xtable"))
• Perl

Optional:

• BLAT or BLAST (to generate alignments against a reference genome). If using BLAT, add faToTwoBit,gfClient,gfServer to your PATH. If using BLAST, add blastall and formatdb.

Edit permute.sh to your liking, paying particular attention to the kmer, cvCut, expCov, and other flags

To Run:

1. perl fastaAllSize mysequences.fa > mysequences.stat or gunzip -c mysequences.fa.gz | fastaAllSize > mysequences.stat Substitute fastqAllSize for fastq files.
2. ./permute.sh mysequences (leave out the .fa)

https://github.com/leipzig/standardized-velvet-assembly-report

Address of the bookmark: https://github.com/leipzig/standardized-velvet-assembly-report

More at https://sourceforge.net/projects/sb2nhri/files/MyPro/

Address of the bookmark: http://www.sciencedirect.com/science/article/pii/S0167701215001207

PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.

Address of the bookmark: http://sco.h-its.org/exelixis/web/software/pear/doc.html

More at http://www.homolog.us/Tutorials/index.php?p=1.4&s=1

Address of the bookmark: http://www.homolog.us/Tutorials/index.php?p=1.4&s=1

Progressive Cactus is a whole-genome alignment package.

Requirements

• git
• gcc 4.2 or newer
• python 2.7
• wget
• 64bit processor and build environment
• 150GB+ of memory on at least one machine when aligning mammal-sized genomes; less memory is needed for smaller genomes.
• Parasol or SGE for cluster support.
• 750M disk space

Instructions

IMPORTANT NOTE: Progressive Cactus does not presently support installation into paths that contain spaces. Until this is resolved, you can use a softlink as a workaround: ln -s "path with spaces" "installation path without spaces"

In the parent directory of where you want Progressive Cactus installed:

git clone git://github.com/glennhickey/progressiveCactus.git
cd progressiveCactus
git pull
git submodule update --init
make

It is also convenient to add the location of progressiveCactus/bin to your PATH environment variable. In order to run the included tools (ex hal2maf) in the submodules/ directory structure, first source progressiveCactus/environment to load the installed environment.

If any errors occur during the build process, you are unlikely to be able to use the tool. Please submit a GitHub issue so we can help out: not only will you help yourself, but others who wish to use the tool as well.

Note that all dependencies are also built and included in the submodules/ directory. This increases the size and build time but greatly simplifies installation and version management. The installation does not create or modify any files outside the progressiveCactus/ directory.

Address of the bookmark: https://github.com/glennhickey/progressiveCactus