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.
Important Note: For conda the channel bioconda needs to be set as highest priority! This is required due to two differnt packages with the same name in different channels. For the pipeline the package jellyfish from the channel bioconda is needed and NOT the jellyfisch package from the channel conda-forge!
nextflow run pipeline.nf --bigwig [BigWig-file] --bed [BED-file] --genome_fasta [FASTA-file] --motif_db [MEME-file] --config [UROPA-config-file]
For a detailed overview for all parameters follow this link.
Required arguments:
--bigwig Path to BigWig-file
--bed Path to BED-file
--genome_fasta Path to genome in FASTA-format
--motif_db Path to motif-database in MEME-format
--config Path to UROPA configuration file
--create_known_tfbs_path Path to directory where output from tfbsscan (known motifs) are stored.
Path can be set as tfbs_path in next run. (Default: './')
--out Output Directory (Default: './out/')
Optional arguments:
--help [0|1] 1 to show this help message. (Default: 0)
--tfbs_path Path to directory with output from tfbsscan. If given tfbsscan will not be run.
Footprint extraction:
--window_length INT This parameter sets the length of a sliding window. (Default: 200)
--step INT This parameter sets the number of positions to slide the window forward. (Default: 100)
--percentage INT Threshold in percent (Default: 0)
Filter unknown motifs:
--min_size_fp INT Minimum sequence length threshold. Smaller sequences are discarded. (Default: 10)
--max_size_fp INT Maximum sequence length threshold. Discards all sequences longer than this value. (Default: 100)
Clustering:
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 Interations 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:
--min_seq INT Sets the minimum number of sequences required for the FASTA-files given to GLAM2. (Default: 100)
--motif_min_key INT Minimum number of key positions (aligned columns) in the alignment done by GLAM2. (Default: 8)
--motif_max_key INT Maximum number of key positions (aligned columns) in the alignment done by GLAM2.f (Default: 20)
--iteration INT Number of iterations done by glam2. More Iterations: better results, higher runtime. (Default: 10000)
--tomtom_treshold float Threshold for similarity score. (Default: 0.01)
--best_motif INT Get the best X motifs per cluster. (Default: 3)
Moitf clustering:
--cluster_motif Boolean If 1 pipeline clusters motifs. If its 0 it does not. (Defaul: 0)
--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:
--organism [hg38 | hg19 | mm9 | mm10] Input organism
--tissues List/String List of one or more keywords for tissue-/category-activity, categories must be specified as in JSON
config
All arguments can be set in the configuration files
For further information read the documentation