De novo motif discovery and evaluation based on footprints identified by TOBIAS
For further information read the documentation
Start with installing all dependencies listed above. It is required to set the enviroment paths for meme-suite. this can be done with following commands:
export PATH=[meme-suite instalation path]/libexec/meme-[meme-suite version]:$PATH
export PATH=[meme-suite instalation path]/bin:$PATH
Download all files from the GitHub repository. The Nextflow-script needs a conda enviroment to run. Nextflow can create the needed enviroment from the given yaml-file. On some systems Nextflow exits the run with following error:
Caused by:
Failed to create Conda environment
command: conda env create --prefix --file env.yml
status : 143
message:
If this error occurs you have to create the enviroment before starting the pipeline. To create this enviroment you need the yml-file from the repository. Run the following commands to create the enviroment:
path=[Path to given masterenv.yml file]
conda env create --name masterenv -f=$path
When the enviroment is created, set the variable 'path_env' in the configuration file as the path to it.
nextflow run pipeline.nf --input [BigWig-file] --bed [BED-file] --genome_fasta [FASTA-file] --jaspar_db [MEME-file]
For a detailed overview for all parameters follow this link.
Required arguments:
--input Path to BigWig-file with scores on the peaks of interest
--bed Path to BED-file with peaks of interest corresponding to the BigWig file
--genome_fasta Path to genome in FASTA-format
--jaspar_db Path to motif-database in MEME-format
--organism STRING Source organism: [ hg19 | hg 38 or mm9 | mm10 ]
Optional arguments:
Footprint extraction:
--window_length INT (Default: 200) a length of a window
--step INT (Default: 100) an interval to slide the window
--percentage INT(Default: 0) a percentage to be added to background while searching for footprints
Filter unknown motifs:
--min_size_fp INT (Default: 10)
--max_size_fp INT (Default: 100)
Cluster:
Sequence preparation/ reduction:
--kmer INT Kmer length (Default: 10)
--aprox_motif_len INT Motif length (Default: 10)
--motif_occurence FLOAT Percentage of motifs over all sequences. Use 1 (Default) to assume every sequence contains a motif.
--min_seq_length INT Remove all sequences below this value. (Default: 10)
Clustering:
--global INT Global (=1) or local (=0) alignment. (Default: 0)
--identity FLOAT Identity threshold. (Default: 0.8)
--sequence_coverage INT Minimum aligned nucleotides on both sequences. (Default: 8)
--memory INT Memory limit in MB. 0 for unlimited. (Default: 800)
--throw_away_seq INT Remove all sequences equal or below this length before clustering. (Default: 9)
--strand INT Align +/+ & +/- (= 1). Or align only +/+ (= 0). (Default: 0)
Motif estimation:
--motif_min_len INT Minimum length of Motif (Default: 8)
--motif_max_len INT Maximum length of Motif (Default: 20)
--interation INT Number of iterations done by glam2. More Interations: better results, higher runtime. (Default: 10000)
--tomtom_treshold float Threshold for similarity score. (Default: 0.01)
Motif clustering:
--edge_weight INT Minimum weight of edges in motif-cluster-graph (Default: 5)
--motif_similarity_thresh FLOAT threshold for motif similarity score (Default: 0.00001)
Creating GTF:
--tissues STRING Filter for tissue/category activity categorys as in JSON config (Default: None)
--wd PATH current working directory for the script (default: ".")
--dir PATH directory for saved Ensembl / UCSC file (default: "./data/")
--out PATH directory for the output GTF (default: ".")
All arguments can be set in the configuration files.
For further information read the documentation