Git Product home page Git Product logo

chester's Introduction

Build Status Codacy Badge License: GPL v3

CHESTER

CHESTER is a probabilistic tool to map and visualize evolutionary regions (relative singularity regions). The references can be non-aligned, such as those outputed directly from NGS plataforms (FASTQ), while the target sequences should be aligned (FASTA). CHESTER has a probabilistic way to detect the relative absense of large k-mer sizes (up to 30), namely using bloom filters. The bloom filters are set automatically.

INSTALLATION

Cmake is needed for installation (CMAKE). You can download it directly from http://www.cmake.org/cmake/resources/software.html or use an appropriate packet manager. In the following instructions we show the procedure to install, compile and run CHESTER:

STEP 1

Download, install and resolve conflicts.

Linux

sudo apt-get install cmake
git clone https://github.com/pratas/chester.git
cd chester/src/
cmake .
make

Alternatively, you can install (without cmake and git, but only for linux) using

wget https://github.com/pratas/chester/archive/master.zip
unzip master.zip
cd chester-master/src/
mv Makefile.linux Makefile
make

OS X

Install brew:

ruby -e "$(curl -fsSL https://raw.github.com/Homebrew/homebrew/go/install)"

only if you do not have it. After type:

brew install cmake
brew install wget
brew install gcc48
wget https://github.com/pratas/chester/archive/master.zip
unzip master.zip
cd chester-master/src/
cmake .
make

With some versions you might need to create a link to cc or gcc (after the brew install gcc48 command), namely

sudo mv /usr/bin/gcc /usr/bin/gcc-old   # gcc backup
sudo mv /usr/bin/cc /usr/bin/cc-old     # cc backup
sudo ln -s /usr/bin/gcc-4.8 /usr/bin/gcc
sudo ln -s /usr/bin/gcc-4.8 /usr/bin/cc

In some versions, the gcc48 is installed over /usr/local/bin, therefore you might need to substitute the last two commands by the following two:

sudo ln -s /usr/local/bin/gcc-4.8 /usr/bin/gcc
sudo ln -s /usr/local/bin/gcc-4.8 /usr/bin/cc

Windows

In windows use cygwin (https://www.cygwin.com/) and make sure that it is included in the installation: cmake, make, zcat, unzip, wget, tr, grep (and any dependencies). If you install the complete cygwin packet then all these will be installed. After, all steps will be the same as in Linux.

EXECUTION

Run CHESTER-map:

./CHESTER-map -v -k 30 -i -s 6099999999 File1.fastq:File2.fastq:File3.fasta FileA.fasta:FileB.fasta

PARAMETERS

To see the possible options type

./CHESTER-map

or

./CHESTER-map -h

These will print the following options:

Usage: CHESTER-map <OPTIONS>... [FILE]:<...> [FILE]:<...>
CHESTER-map: a tool to map relative singularity regions  
The (probabilistic) Bloom filter is automatically set.

  -v                       verbose mode,             
  -a                       about CHESTER,            
  -s <value>               bloom size,               
  -i                       use inversions,           
  -p                       show positions/words,
  -k <value>               k-mer size (up to 30),               
                                                     
  [rFile1]:<rFile2>:<...>  reference file(s),   
  [tFile1]:<tFile2>:<...>  target file(s).           

The reference files may be FASTA, FASTQ or DNA-SEQ,
while the target files may be FASTA or DNA-SEQ.
Report bugs to <{pratas,ap,pjf}@ua.pt>. 

Most of the values are set automatically.

For CHESTER-filter type:

./CHESTER-filter

while for CHESTER-visual type:

./CHESTER-visual

EXAMPLE

The following illustrate a Human-Neanderthal example. For the purpose go to the base and run:

cp ancient/runNeanderthalGRC37.sh .
. RunNeanderthalGRC73.sh &

It will download all the sequences and run CHESTER-map. This will output the plot.svg, with the human novel regions relatively to the Neanderthal, chromosome by chromosome. The next image illustrate such result:

CHESTER

CITATION

On using this software/method please cite:

D. Pratas, M. Hosseini, R. M. Silva, A. J. Pinho, P. J. S. G. Ferreira. Visualization of Distinct DNA Regions of the Modern Human Relatively to a Neanderthal Genome. Iberian Conference on Pattern Recognition and Image Analysis. Springer, Cham, 2017.

D. Pratas, R. M. Silva, A. J. Pinho, P. J. S. G. Ferreira. Detection and visualisation of regions of human DNA not present in other primates. Proceedings of the 21st Portuguese Conference on Pattern Recognition, RecPad 2015, Faro, Portugal, October 2015.

ISSUES

For any issue let us know at issues link.

LICENSE

GPL v3.
For more information:

http://www.gnu.org/licenses/gpl-3.0.html

chester's People

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

Forkers

ieeta-pt

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.