Only the most essentials are kept, mostly explanation of installation errors and how to fix them. For detailed instructions, please refer to Funseq2 Protocol.
It’s recommended to install things to a designated Conda environment, for some tools, I will only list Conda installation command.
Dependances to install first
– TPMpvalue [link]
– Perl package Parallel::ForkManager [link]
– VAT (snpMapper, indelMapper Module) [link]
– sed/awk/grep (those should have been pre-installed already)
Download the TFM-Pvalue.tar.gz from its website,
tar -xf TFM-Pvalue.tar.gz to decompress the package and
cd into the folder. To compile the package type as follow.
tar -xf TFM-Pvalue.tar.gz cd TFM-Pvalue make
After compiling the tool successfully, either directly copy the compiled binary files into your
/usr/bin folder, or add the path to the environmental variable as below.
g++ -O3 -DJASPAR=1 -DPROGRAM=0 TFMpvalue.cpp Matrix.cpp ArgumentException.cpp FileException.cpp ParseException.cpp -o TFMpvalue-pv2sc
TFMpvalue.cpp: In function ‘void arguments(int, char* const*)’:
TFMpvalue.cpp:503:45: error: ‘getopt’ was not declared in this scope
TFM-Pvaluefolder, find the file
TFPpvaue.cpp, uncomment line 16 in that file and change
Perl package Parallel::ForkManager
Here is the installation using Conda.
conda install -n yourEnvr -c bioconda perl-parallel-forkmanager
Installation using Conda.
conda install -n yourEnvr -c bioconda bedtools conda install -n yourEnvr -c bioconda tabix conda install -n yourEnvr -c bioconda ucsc-bigwigaverageoverbed
The easiest way is to download pre-built binaries, save them into your local
/usr/bin/ or add the path to your environmental variable and make them executable.
export PATH=$PATH:/where/you/put/binary/files chmod +x snpMapper chmod +x indelMapper # <- to make them executable
Download the Funseq2 and pre-processed data
Download the Funse2 from its newest update:
Download the latest data needed for Funseq2 and put everything into the
data_context folder, unzip
XXX.tar.gz folders within
You can also download an older build of the data set from https://khuranalab.med.cornell.edu/data.html
The content can be downloaded in a compressed folder from that page.
Prepare funseq2.sh and config.txt file to run Funseq2
FunSeq2_DC folder, you need to modify two files before starting:
### In funseq2.sh ### # keep "data_context/user_annotations" intact user_anno=/your/destination/of/data_context/user_annotations ### In contig.txt ### # Change the file path first and then change the annotation files you want to use accordingly. file_path=/your/destination/of/data_context
user_annocan be specified in the running command by using the option
-ua. But if you don’t want to type that every time, you can just change it in funseq2.sh.
If running on cluster and using Conda, remember to export the
After all the preparation, we are finally here. To run FunSeq2 is simple.
funseq2.sh -f file -maf MAF -m <1/2> -len length_cut -inf <bed/vcf> -outf <bed/vcf> -nc -o path -g file -exp file -cls file -exf <rpkm/raw> -p int -cancer cancer_type -s score -uw -ua user_annotations_directory -db