Genotype and SNP-calling from Next-Generation Sequencing data
April 2, 2012
The step-by-step instructions for classroom exercises can be found at this workshop site. Below are the instructions for downloading data to get an early start.
dirty_src/: This contains the sources used for building the program
precompiled/: This contains precompiled binary files for X32 and X64. For UNIX we have also compiled the programs staticly in case you have problems. For OSX we have only compiled it for 32bit.
LCT.data/: datafiles containing data surrounding the LCT region, for 25 danes
exampleOutput/: This is output of the programs generated if you follow this website. Use this if you for some reason have problems running the program
simulated.data/: This contains simulated data ready to be used for PCA analysis.
INSTALLATION
You unpack the .tar.gz with tar xfvz workshop.tar.gz tar xfvz simulated.data.tar.gz
then move everything is a single folder cp -R simulated.data rasmus.workshop rm -r simulated.data
This creates the folder called rasmus.workshop. Move into this folder. cd rasmus.workshop/
We will use 2 programs, 'dirty' and 'optimSFS', and several R scripts.
We can use the precompiled binaries or we can build the programs our selves. In either case we will need to have these program in the root of the unpacked folder.
1) Using precompiled binaries: You can simply copy or make links to the precompiled files in the appropiate subdirectory in the precompiled folder:
ln -fs precompiled/linux/optimSFS.x32 optimSFS ln -fs precompiled/linux/dirty.x32 dirty
The above is for a Linux 32bit platform, which should also work for linux 64bit platform.
For OSX the commands would be ln -fs precompiled/osx/optimSFS.x32 optimSFS ln -fs precompiled/osx/dirty.x32 dirty
If there are problems due to missing shared object files, you can try the files in the 'precompiled/linux.static/' directory, which 'should' be standalone without any dependencies.
2) Building source files
If the precompiled won't run you can compile it for youself. This will be done for you, along with creating appropiate symlinks to the correct files with: ./install.sh
If for some reason this won't work. Then try first: cd dirty_src/;make clean ;cd misc;make clean ;cd ../samtools-0.1.17/;make clean;cd ../../;
And then try recompiling cd dirty_src/misc ;make ; cd ../samtools-0.1.17/;make ;cd ..;make;cd ..;
And now we make symlinks to the executables ln -fs dirty_src/misc/optimSFS.gcc optimSFS ln -fs dirty_src/dirty/dirty.g++ dirty
If everything went fine, when you type ./dirty or ./optimSFS you should get some info messages.
If you have problems or questions on downloading data or installing programs, please let me know matteo.fumagalli@berkeley.edu. Any way, we are gonna guide the installation step by step during the workshop.
Genotype and SNP-calling from Next-Generation Sequencing data
April 2, 2012
The step-by-step instructions for classroom exercises can be found at this workshop site. Below are the instructions for downloading data to get an early start.
Note: This has only been tested on Linux and OSX.
This workshop will guide you through some basic exercises using the program called 'dirty' and R http://www.r-project.org/. Please go to R Project web site to download the program.
The data needed for this tutorial is in two tar.gz files, that you can download here http://palin.popgen.dk/thorfinn/workshopApril/workshop.tar.gz and here http://palin.popgen.dk/thorfinn/workshopApril/simulated.data.tar.gz.
CONTENTS
INSTALLATION
You unpack the .tar.gz with
tar xfvz workshop.tar.gz
tar xfvz simulated.data.tar.gz
then move everything is a single folder
cp -R simulated.data rasmus.workshop
rm -r simulated.data
This creates the folder called rasmus.workshop. Move into this folder.
cd rasmus.workshop/
We will use 2 programs, 'dirty' and 'optimSFS', and several R scripts.
We can use the precompiled binaries or we can build the programs our selves. In either case we will need to have these program in the root of the unpacked folder.
1) Using precompiled binaries: You can simply copy or make links to the precompiled files in the appropiate subdirectory in the precompiled folder:
ln -fs precompiled/linux/optimSFS.x32 optimSFSln -fs precompiled/linux/dirty.x32 dirty
The above is for a Linux 32bit platform, which should also work for linux 64bit platform.
For OSX the commands would be
ln -fs precompiled/osx/optimSFS.x32 optimSFS
ln -fs precompiled/osx/dirty.x32 dirty
If there are problems due to missing shared object files, you can try the files in the 'precompiled/linux.static/' directory, which 'should' be standalone without any dependencies.
2) Building source files
If the precompiled won't run you can compile it for youself. This will be done for you, along with creating appropiate symlinks to the correct files with:./install.sh
If for some reason this won't work. Then try first:
cd dirty_src/;make clean ;cd misc;make clean ;cd ../samtools-0.1.17/;make clean;cd ../../;
And then try recompiling
cd dirty_src/misc ;make ; cd ../samtools-0.1.17/;make ;cd ..;make;cd ..;
And now we make symlinks to the executables
ln -fs dirty_src/misc/optimSFS.gcc optimSFS
ln -fs dirty_src/dirty/dirty.g++ dirty
If everything went fine, when you type ./dirty or ./optimSFS you should get some info messages.
If you have problems or questions on downloading data or installing programs, please let me know matteo.fumagalli@berkeley.edu. Any way, we are gonna guide the installation step by step during the workshop.