Introduction Usage Parameters Output Results Releases

Define where the pipeline should find input data and save output data.

Input sample sheet (raw / mzML)

required
type: string
default: false

Use this to specify a sample sheet table including your input raw or mzml files as well as their metainformation such as BatchID and MSstats_Condition. For example:

| Sample | BatchID | MSstats_Condition | Spectra_Filepath |
| -----|:------------:| ----------:|------------------------------------------:|
| 1 | MelanomaStudy | Malignant | data/Melanoma_DIA_standard.raw |
| 2 | MelanomaStudy | Benign | data/SkinTissue_DIA_standard.raw |
| 3 | BreastCancerStudy | Malignant | data/BraCa_DIA_standard.raw |
| 4 | BreastCancerStudy | Benign | data/BreastTissue_DIA_standard.raw |

Input sample sheet of spectral libraries (tsv, pqp, TraML)

type: string

Use this to specify a sample sheet table including your input spectral library files as well as their metainformation such as BatchID and MSstats_Condition. For example:

| Sample | BatchID | Library_Filepath |
| -----|:------------:|------------------------------------------:|
| 1 | MelanomaStudy | data/Melanoma_library.tsv |
| 2 | BreastCancerStudy | data/BraCa_library.tsv |

Path to internal retention time standard sample sheet (tsv, pqp, TraML)

type: string

Use this to specify a sample sheet table including your input internal retention time spectral library files as well as their metainformation such as BatchID and MSstats_Condition. For example:

| Sample | BatchID | irt_Filepath |
| -----|:------------:|------------------------------------------:|
| 1 | MelanomaStudy | data/Melanoma_irt_library.tsv |
| 2 | BreastCancerStudy | data/BraCa_irt_library.tsv |

The output directory where the results will be saved.

type: string
default: ./results

Set this flag if output plots should be generated.

type: boolean
default: true
  1. BarChartProtein/Peptide Counts
  2. Pie Chart: Peptide Charge distribution
  3. Density Scatter: Library vs run RT deviations for all identifications
  4. Heatmap: Peptide quantities across MS runs
  5. Pyprophet score plots

In addition MSstats will run and export comparative protein statistics plots such as Volcano plots if protein level is specified.

Set this flag if statistical normalization and visualizations should be generated using MSstats

type: boolean

Email address for completion summary.

type: string
pattern: ^([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.

Set this flag if the spectral library should be generated using EasyPQP from provided DDA data - identification search results and corresponding raw data.

type: boolean
default: false

Input sample sheet to use for library generation eg. DDA raw data (mzML) and DDA identification data (pepXML, mzid, idXML)

type: string

Use this to specify a sample sheet table including your input DDA raw or mzml files as well as their corresponding peptide identification files and BatchID metainformation. For example:

| Sample | BatchID | Spectra_Filepath | Id_Filepath |
| -----|:------------:| ----------:|------------------------------------------:|
| 1 | MelanomaStudy | data/Melanoma_DDA_rep1.mzML | data/Melanoma_DDA_rep1.pepXML |
| 2 | MelanomaStudy | data/Melanoma_DDA_rep2.mzML | data/Melanoma_DDA_rep2.pepXML |
| 3 | BreastCancerStudy | data/BraCa_DDA_rep1.mzML | data/BraCa_DDA_rep1.pepXML |
| 4 | BreastCancerStudy | data/BraCa_DDA_rep2.mzML | data/BraCa_DDA_rep2.pepXML |

PSM fdr threshold to align peptide ids with reference run.

type: number
default: 0.01

Minimum number of transitions for assay

type: integer
default: 4

Maximum number of transitions for assay

type: integer
default: 6

Method for generating decoys

type: string

Set this flag if using a spectral library that already includes decoy sequences and therefor skip assay and decoy generation.

type: boolean
default: false

Path to unimod file needs to be provided

type: string
default: https://raw.githubusercontent.com/nf-core/test-datasets/diaproteomics/unimod.xml

Example file:
https://raw.githubusercontent.com/nf-core/test-datasets/diaproteomics/unimod.xml

Set this flag if pseudo internal retention time standards should be generated using EasyPQP from provided DDA data - identification search results and corresponding raw data.

type: boolean
default: false

Number of pseudo irts selected from dda identifications based on the best q-value

type: integer
default: 250

Set this flag if the libraries defined in the input or by generation should be merged according to the SampleID

type: boolean
default: false

Set this flag if pairwise RT alignment should be applied to libraries when merging.

type: boolean
default: false

Minimum number of peptides to compute RT alignment during pairwise merging of libraries

type: integer
default: 100

Mass tolerance for transition extraction (ppm)

type: integer
default: 30

Mass tolerance for precursor transition extraction (ppm)

type: integer
default: 10

RT window for transition extraction (seconds)

type: integer
default: 600

Minimal random mean squared error for irt RT alignment

type: number
default: 0.95

Number of bins defined for the RT Normalization

type: integer
default: 10

Number of bins that have to be covered for the RT Normalization

type: integer
default: 8

Method for irt RT alignment for example

type: string

Force the analysis of the OpenSwathWorkflow despite severe warnings

type: boolean
default: false

Machine learning classifier used for pyprophet target / decoy separation

type: string

MS Level of pyprophet FDR calculation

type: string

Abstraction level of pyrophet FDR calculation

type: string

Threshold for pyprophet FDR filtering on peakgroup abstraction level

type: number
default: 0.01

Threshold for pyprophet FDR filtering on peptide abstraction level

type: number
default: 0.01

Threshold for pyprophet FDR filtering on protein abstraction level

type: number
default: 0.01

Start for pyprophet non-parametric pi0 estimation

type: number
default: 0.1

End for pyprophet non-parametric pi0 estimation

type: number
default: 0.5

Steps for pyprophet non-parametric pi0 estimation

type: number
default: 0.05

DIAlignR global alignment FDR threshold: After the chromatogram alignment all peaks should still satisfy the global alignment FDR threshold.

type: number
default: 0.01

DIAlignR analyte FDR threshold: Before the chromatogram alignment only peaks satusfying this threshold will be matched across runs.

type: number
default: 0.01

DIAlignR unalignment FDR threshold: Before the chromatogram alignment only peaks satisfying this threshold will be matched across runs.

type: number
default: 0.01

DIAlignR alignment FDR threshold: After the chromatogram alignment aligned peaks should satisfy this threhold.

type: number
default: 0.05

DIAlignR query FDR threshold: During the chromatogram alignment ponly eaks satisfying this maximum FDR threshold will be considered as potential matches.

type: number
default: 0.05

Options for the reference genome indices used to align reads.

Directory / URL base for iGenomes references.

hidden
type: string
default: s3://ngi-igenomes/igenomes/

Do not load the iGenomes reference config.

hidden
type: boolean

Do not load igenomes.config when running the pipeline. You may choose this option if you observe clashes between custom parameters and those supplied in igenomes.config.

Less common options for the pipeline, typically set in a config file.

Display help text.

hidden
type: boolean

Method used to save pipeline results to output directory.

hidden
type: string

The 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.

Workflow name.

hidden
type: string

A custom name for the pipeline run. Unlike the core nextflow -name option with one hyphen this parameter can be reused multiple times, for example if using -resume. Passed through to steps such as MultiQC and used for things like report filenames and titles.

Email address for completion summary, only when pipeline fails.

hidden
type: string
pattern: ^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$

This works exactly as with --email, except emails are only sent if the workflow is not successful.

Send plain-text email instead of HTML.

hidden
type: boolean

Set to receive plain-text e-mails instead of HTML formatted.

Do not use coloured log outputs.

hidden
type: boolean

Set to disable colourful command line output and live life in monochrome.

Directory to keep pipeline Nextflow logs and reports.

hidden
type: string
default: ${params.outdir}/pipeline_info

Set the top limit for requested resources for any single job.

Maximum number of CPUs that can be requested for any single job.

hidden
type: integer
default: 16

Use to set an upper-limit for the CPU requirement for each process. Should be an integer e.g. --max_cpus 1

Maximum amount of memory that can be requested for any single job.

hidden
type: string
default: 128.GB

Use to set an upper-limit for the memory requirement for each process. Should be a string in the format integer-unit e.g. --max_memory '8.GB'

Maximum amount of time that can be requested for any single job.

hidden
type: string
default: 240.h

Use to set an upper-limit for the time requirement for each process. Should be a string in the format integer-unit e.g. --max_time '2.h'

Parameters used to describe centralised config profiles. These should not be edited.

Git commit id for Institutional configs.

hidden
type: string
default: master

Provide git commit id for custom Institutional configs hosted at nf-core/configs. This was implemented for reproducibility purposes. Default: master.

## Download and use config file with following git commit id  
--custom_config_version d52db660777c4bf36546ddb188ec530c3ada1b96

Base directory for Institutional configs.

hidden
type: string
default: https://raw.githubusercontent.com/nf-core/configs/master

If 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 the custom_config_base option. For example:

## Download and unzip the config files  
cd /path/to/my/configs  
wget https://github.com/nf-core/configs/archive/master.zip  
unzip master.zip  
  
## Run the pipeline  
cd /path/to/my/data  
nextflow run /path/to/pipeline/ --custom_config_base /path/to/my/configs/configs-master/

Note that the nf-core/tools helper package has a download command to download all required pipeline files + singularity containers + institutional configs in one go for you, to make this process easier.

Institutional configs hostname.

hidden
type: string

Institutional config description.

hidden
type: string

Institutional config contact information.

hidden
type: string

Institutional config URL link.

hidden
type: string
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