stats_metricsinroi

Module to compute statistics (mean, std) of scalar maps (metrics), which can represent diffusion metrics, in ROIs or labels.

Keywords : nifti, volume, scilpy, stats, rois

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Inputs

Input 1

Format : tuple val(meta), path(metrics), path(rois), path(rois_lut)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
metrics	file	Metrics volume(s) in Nifti	True	*.{nii,nii.gz}
rois	file	ROI or Label volume(s) in Nifti	True	*.{nii,nii.gz}
rois_lut	file	LUT file corresponding to labels, used to name the regions of interest	False	*.{nii,nii.gz}

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Outputs

stats_json

Format : tuple val(meta), path(*.json)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*.json	file	JSON file containing mean/std per pair of roi/metrics or label/metrics	True	*.json

stats_mean

Format : tuple val(meta), path(*_desc-mean_*.{csv,tsv})

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
desc-mean.{csv,tsv}	file	Tabular file containing rows of (sample, roi, mean_metric1, mean_metric2, …). Can be either TSV or CSV depending on the output_format argument.	True	*_desc-mean_*.{csv,tsv}

stats_std

Format : tuple val(meta), path(*_desc-std_*.{csv,tsv})

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
desc-std.{csv,tsv}	file	Tabular file containing rows of (sample, roi, std_metric1, std_metric2, …). Can be either TSV or CSV depending on the output_format argument.	True	*_desc-std_*.{csv,tsv}

versions

Format : path(versions.yml)

	Type	Description	Mandatory	Pattern
versions.yml	file	File containing software versions	True	versions.yml

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Arguments (see process.ext)

	Type	Description	Default	Choices
suffix	string	It will add an extra string before “_stats.json”
bin	boolean	If set, will consider every value of the mask higherthan 0 to be part of the mask (equivalent weighting for every voxel). It will be used if use_label is false.	False
normalize_weights	boolean	If set, the weights will be normalized to the [0,1] range. It will be used if use_label is false.	False
use_label	boolean	If set, rois image will be considered as a label image with multiple indices.	False
key_substrs_to_remove	string	Groovy list of strings to remove from the metric keys in the JSON. This is useful to clean or shorten the bundle names that will appear in the output JSON/CSV. e.g. ”[‘_mask’, ‘_warped’] will turn ‘CST_mask_warped’ into ‘CST‘“	None
value_substrs_to_remove	string	Groovy list of strings to remove from the metric values in the JSON. This is useful to clean or shorten the metric names that will appear in the output JSON/CSV. e.g. ”[‘sub-01’, ‘_metric’] will turn ‘sub-01_fa_metric’ into ‘fa‘“	None
output_format	string	Output format for the tabular stats file.	tsv	- csv - tsv
meta_columns	list	List of keys from the meta map to add as extra columns in the tabular stats files. e.g. ['age', 'laterality'] will add two columns with the corresponding names and values for each sample taken from the input meta map. This is particularly useful to add covariates such as the age, laterality, diagnosis, etc. of each subject. If the key is not found in the meta map, an empty value will be used.	[]

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Tools

	Description	DOI
scilpy	The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox.

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Authors

• @arnaudbore

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Last updated : 2025-12-22