nf-core/metapep
From metagenomes to epitopes and beyond
Define where the pipeline should find input data and save output data.
Path to comma-separated file containing information about the samples in the experiment.
string^\S+\.csv$You will need to create a design file with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row. See usage docs.
The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
stringEmail address for completion summary.
string^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file (~/.nextflow/config) then you don't need to specify this on the command line for every run.
MultiQC report title. Printed as page header, used for filename if not otherwise specified.
stringParameters used to describe centralised config profiles. These should not be edited.
Git commit id for Institutional configs.
stringmasterBase directory for Institutional configs.
stringhttps://raw.githubusercontent.com/nf-core/configs/masterIf you're running offline, Nextflow will not be able to fetch the institutional config files from the internet. If you don't need them, then this is not a problem. If you do need them, you should download the files from the repo and tell Nextflow where to find them with this parameter.
Institutional config name.
stringInstitutional config description.
stringInstitutional config contact information.
stringInstitutional config URL link.
stringbooleantrueLess common options for the pipeline, typically set in a config file.
Display version and exit.
booleanMethod used to save pipeline results to output directory.
stringThe Nextflow publishDir option specifies which intermediate files should be saved to the output directory. This option tells the pipeline what method should be used to move these files. See Nextflow docs for details.
Email address for completion summary, only when pipeline fails.
string^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$An email address to send a summary email to when the pipeline is completed - ONLY sent if the pipeline does not exit successfully.
Send plain-text email instead of HTML.
booleanFile size limit when attaching MultiQC reports to summary emails.
string25.MB^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$Do not use coloured log outputs.
booleanIncoming hook URL for messaging service
stringIncoming hook URL for messaging service. Currently, MS Teams and Slack are supported.
Custom config file to supply to MultiQC.
stringCustom logo file to supply to MultiQC. File name must also be set in the MultiQC config file
stringCustom MultiQC yaml file containing HTML including a methods description.
stringBoolean whether to validate parameters against the schema at runtime
booleantrueBase URL or local path to location of pipeline test dataset files
stringhttps://raw.githubusercontent.com/nf-core/test-datasets/Define pipeline options.
Minimum length of produced peptides.
integer9Maximum length of produced peptides.
integer11Only takes effect for pred_method 'syfpeithi'. Allow all peptide lengths within the range of min_pep_len to max_pep_len without reducing them to the matching allele models.
booleanEpitope prediction method to use
stringThreshold for binder/non-binder calling when using SYFPEITHI epitope prediction method.
number0.5Threshold for binder/non-binder calling when using MHCflurry or MHCnuggets epitope prediction methods. The default value of 0.426 corresponds to an IC50 of ≤500.
number0.426Display supported alleles of all prediction methods and exit.
booleanProdigal mode, 'meta' or 'single'.
stringmetaEnables "deep" memory usage output for main DataFrames generated in pandas scripts ("deep" ensures accurate usage values, but slightly increases runtime).
booleanMaximum chunk size (#peptides) for epitope prediction jobs.
integer4000000Scaling factor for prediction_chunk_size parameter for usage in python scripts to reduce memory usage when handling DataFrames.
integer10Maximum chunk size (#epitope predictions) for processing of downstream visualisations.
integer7500000Maximum number of tasks submitted by PREDICT_EPITOPES process
integer1000Number of files, which are merged in MERGE_PREDICTION_BUFFER
integer1000Do not display mean comparison p-values in boxplots.
boolean