W: Group statistics of mass spectra (multi-dataset)
Brief description
Compute ion statistics such as p- and q-values, volcano plots, and many other metrics across groups. This will calculate 'group' statistics to give you an idea of 'significant' features across conditions.
Parameters
Tag (identifier) (type - string)
Tag to use to help identify object.
Normalization tag (type - string)
Tag to use for normalization.
Help
Rather than applying a normalization to the entire dataset, we apply it as needed to each task at hand.
You can compare the effect normalization has on specific task by repeating it with different normalization.
In some cases, its advised to use 'multi-dataset' normalization, in particular when doing comparisons.
Normalization name (type - string)
Name of the normalization.
Include tags (type - array)
Tags to use for comparisons.
No. of bootstrap samples (type - integer)
Number of bootstrap samples to use for p-value estimation.
Plot style (type - array)
Style of the generated figures.
Export images as (type - string)
Export figures as image or within a single PDF or PowerPoint.
m/zs (type - array)
M/z values.
Filename (type - string)
Path to peaklist file.
Mask (type - string)
Mask to use for sampling the input data. If a mask is not specified, an equally spaced selection of pixels will be used to calculate the statistics. If a mask is specified, a random subset of pixels will be used to calculate the statistics.
No. of spectral samples (type - integer)
Number of spectral samples when accumulating ion statistics. Value of 1 means that the average spectrum is used.
Neighbourhood radius (type - integer)
Radius to use for the neighbourhood. Value of 0 means that the current pixel is used. Value of 1 means that the current pixel and its 8 neighbours are used, 2 means that the current pixel and its 24, etc.
Reduce method (type - string)
The method to use for reducing the multi-entry data into a single value. For example. if there are several entries for a single m/z, they need to be simplified to calculate boostrap statistics.
Collection method (type - string)
Determines how data should be collected for the list of m/zs. Each method has its advantages and disadvantages.
centroid - use single centroid entry for each m/z
centroid_integrated - use integrated centroid entry for each m/z using the ppm tolerance
detected - use all detected entries for each m/z
direct - use all direct entries for each m/z
direct_integrated - use integrated direct entries for each m/z using the ppm tolerance
Integration ppm (type - number)
ppm tolerance for integration.
Dependencies (other tasks that this task might depend on)
| Depends on | Required/Optional |
|---|---|
| P: Normalization (single-dataset) | optional |
| P: Normalization (multi-dataset) | optional |
| P: Normalization (merged-project) | optional |
| W: M/z feature detection (single-dataset) | optional |
| W: M/z feature detection (multi-dataset) | optional |
| W: Ion mobility feature detection (single-dataset) | optional |
Attributes
| Attribute | Value | Description |
|---|---|---|
| Multiple allowed | True | Allow multiple instances of this task in a workflow. |
| Task can fail | True | Task is optional and can fail without causing the entire workflow to fail. |
| Step can fail | True | Sub-tasks of this task can fail without causing the entire task (and workflow) to fail. |
| Requires ion mobility | False | Task requires ion mobility data. |
| Task can fail (with ion mobility) | False | This task uses ion mobility data but it is allowed to fail, without causing the entire workflow to fail. |
| Allowed in reference dataset | True | Task is to be performed on a 'reference' dataset. This will allow for multiple analyses to be performed on the same dataset, without cluttering or duplicating certain tasks (unused at the moment). |