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drugresponseeval

nf-core/drugresponseeval

This pipeline evaluates drug response models in various settings on a variety of datasets.

version1.4.0f16f63aa8dNov 7, 2026 Upstream Usage docs

Key tools

DrEvalPyCurveCuratorDIPKMOLIMORGOTHSRMFSuperFELT

Parameters

Groups

nf-core modules

Samplesheet cols

Run it

nfclaw

nfclaw run drugresponseeval --outdir results -profile docker

raw nextflow

nextflow run pipelines/drugresponseeval/upstream -profile docker --outdir results

demo · bundled test profile

nfclaw run drugresponseeval --demo --outdir results   # adds the upstream test profile (-profile test,docker)

Inputs

This pipeline does not use a samplesheet; configure inputs via parameters.

Resources

Resource requests follow the pipeline's configs and selected profiles. nf-core's resource labels often assume a server — a single step can request far more memory than a workstation has, and retry rules can increase requests. If a run fails with Process requirement exceeds available memory (or CPUs), cap every request, and every retry, at what this machine actually has:

bash

nfclaw run drugresponseeval --outdir results -profile docker \
  --limit-cpus 4 --limit-memory 15.GB

nfclaw turns those into Nextflow's process.resourceLimits and passes them as a -c config — the mechanism nf-core prescribes for exactly this (docs). Set them to the machine's real capacity. --limit-time DURATION also caps how long any one task may run: a task that needs longer is stopped, and so is every retry, so set it only as a deliberate ceiling, never as a guess at how long the analysis takes. The generated config is kept in <outdir>/provenance/, so commands.sh replays the run under the same ceiling.

Nextflow engine

This release declares nextflowVersion = '!>=26.04.0'.

To pin this release's declared minimum engine — useful when a newer Nextflow has incompatible config parsing:

bash

nfclaw run drugresponseeval ... --nxf-ver 26.04.0

--nxf-ver is recorded in <outdir>/provenance/, so the replay uses the same engine. See known-issues.

Demo

bash

nfclaw run drugresponseeval --demo --outdir results   # adds the upstream test profile (-profile test,docker)

Required parameters

--modelsstring

Model to be tested.

--baselinesstring

Baselines to be tested.

--run-idstring

Run name for the pipeline. The subdirectory in results will be named like this.

--dataset-namestring

Name of the dataset. Pre-supplied datasets are CTRPv2, CTRPv1, CCLE, GDSC1, GDSC2, TOYv1, TOYv2, BeatAML2, and PDX_Bruna.

--outdirstring (directory path)

The output directory where the results will be saved. Default is results/

--test-modestring

Run the pipeline in test mode LPO (Leave-random-Pairs-Out), LCO (Leave-Cell-line-Out), LTO (Leave-Tissue-Out), or LDO (Leave-Drug-Out).

Constraint · matches ^((LPO|LCO|LTO|LDO)?,?)*(?<!,)$

Parameter explorer

41 parameters · 9 groups

Every parameter from the pinned nextflow_schema.json. nfclaw checks explicit values before launch; complex rules use the pinned pipeline's runtime validation. Search, filter by group, and expand any parameter for its default, allowed values and constraints.

Groups

nextflow_schema.json

27 parameters · 14 hidden

Additional options10

Keep only drugs whose fraction of significant responder curves is at least this value.

Keep only drugs with at least this many reproducible responder curves.

Path to a Python script with a custom CV splitter.

Train final model on full data.

Model checkpoint directory

Number of cross-validation splits.

Disable hyperparameter tuning.

False by default (=refitting). By default, we use measures calculated with CurveCurator instead of original measures reported by the authors for the available datasets, or invoke automatic fitting of custom raw viability data with CurveCurator. Set this flag to disable this option.

Optimization metric for the pipeline.

Response transformation

Data options4

Datasets for cross-study prediction.

The name of the drug response measure to use.

Path to the data directory.

Link to the latest Zenodo version of the dataset.

Generic options3

Display the help message.

Display the full detailed help message.

Display hidden parameters in the help message (only works when --help or --help_full are provided).

Input Output options4

Name of the dataset. Pre-supplied datasets are CTRPv2, CTRPv1, CCLE, GDSC1, GDSC2, TOYv1, TOYv2, BeatAML2, and PDX_Bruna.

Email address for completion summary.

The output directory where the results will be saved. Default is results/

Run name for the pipeline. The subdirectory in results will be named like this.

Mode options1

Run the pipeline in test mode LPO (Leave-random-Pairs-Out), LCO (Leave-Cell-line-Out), LTO (Leave-Tissue-Out), or LDO (Leave-Drug-Out).

Model options2

Baselines to be tested.

Model to be tested.

Randomization options2

Randomization mode for the pipeline.

Randomization type for the pipeline.

Robustness options1

Number of trials to run for the robustness test

Outputs

Results land in --outdir; the files and directory layout depend on the selected workflow, parameters and publication settings. Run metadata is normally placed in <outdir>/pipeline_info/ (execution report, software versions), when those outputs are enabled. nfclaw run also writes <outdir>/provenance/ with the exact params file and the run log, <outdir>/provenance/logs/run.log — the whole launch, whose last line states the outcome (Nextflow's own log is <outdir>/.nextflow.log); unless --no-provenance it adds a run manifest (pinned version, commit and exact command), input/output SHA-256 checksums, and a replayable commands.sh. The exact output files and directory layout for this release are documented upstream: github.com/nf-core/drugresponseeval/blob/1.4.0/docs/output.md Check a run — in the foreground or the background — with nfclaw status <outdir>: success, still running, how it ended (with the error), or stopped without an outcome; exit 0 success, 3 running, 1 otherwise.