msPurity.frag4feature (version 1.16.2+galaxy1)

xcmsSet object:

grouped xcmsSet object saved as 'xset' in an RData file

purityA object:

purityA object generated from msPurity_purityA. Contains details of fragmentation spectra and precursor ion purity results (output from purityA tool)

ppm error tolerance between precursor mz and XCMS feature mz:

Fragmentation will be ignored if the precursor mz value is not within the ppm error tolerance to the XCMS feature mz

Precursor ion purity threshold:

Fragmentation will be ignore if the precursor ion purity is less than the threshold (further filtering on the precursor ion purity can be done at the averaging stage if required).

Should the most intense precursor be used within the isolation window?:

If TRUE the most intense precursor will be used. If FALSE the precursor closest to the center of the isolation window will be used

Was retention time correction used?:

If retention time correction has been used in XCMS set this to yes

For matching fragmentation to a feature, use the grouped feature range:

For special cases where the MS2 files have no MS1 data or if the MS1 data in the MS2 file is unreliable

Resubmit your dataset:

Use only if you get a message which say that your original dataset or dataset collection can not be found the server.

Link fragmentation spectra to XCMS features

Description

General

Tool to Assign fragmentation spectra (MS/MS) stored within a purityA class object to grouped features within an XCMS xset object.

Please note that the xcmsSet object needs to have been grouped.

The data inputs are:

A purityA object (generated from purityA) saved in an rdata file.
A xcmsSet grouped object (generated from xcms_group) saved in an rdata file
[optional] a dataset collection of the mzML files to resubmit

XCMS calculates individual chromatographic peaks for each mzML file (saved in xset@peaks), these are then grouped together (using xcms.group). Ideally the mzML files that contain the MS/MS spectra also contain sufficient MS1 scans for XCMS to detect MS1 chromatographic features. If this is the case, to determine if a MS2 spectra is to be linked to an XCMS grouped feature, the associated acquisition time of the MS/MS event has to be within the retention time window defined for the individual peaks associated for each file. The precursor m/z value also has to be within the user ppm tolerance to XCMS feature.

See below for representation of the linking (the *------* represent a many-to-many relationship) e.g. 1 or more MS/MS events can be linked to 1 or more individual feature and an individual XCMS feature can be linked to 1 or more grouped XCMS features

[grouped XCMS feature - across files] *------* [individual XCMS feature - per file] *------* [MS/MS spectra]

Alternatively, if the "useGroup" argument is set to TRUE, the full width of the grouped peak (determined as the minimum rtmin and maximum rtmax of the all associated individual peaks) will be used. This option should be used if the mzML file with MS/MS has very limited MS1 data and so individual chromatographic peaks might not be detected with the mzML files containing the MS/MS data. However, it should be noted this may lead to potential inaccurate linking.

[grouped XCMS peaks] *------* [MS/MS spectra]

Example LC-MS/MS processing workflow

Purity assessments
- (mzML files) -> purityA -> (pa)
XCMS processing
- (mzML files) -> xcms.xcmsSet -> xcms.merge -> xcms.group -> xcms.retcor -> xcms.group -> (xset)
Fragmentation processing
- (xset, pa) -> frag4feature -> filterFragSpectra -> averageAllFragSpectra -> createDatabase -> spectralMatching -> (sqlite spectral database)

Additional notes

If using only a single file, then grouping still needs to be performed within XCMS before frag4feature can be used.
Fragmentation spectra below a certain precursor ion purity can be be removed (see plim argument).
A SQLite database can be created directly here but the functionality has been deprecated and the createDatabase function should now be used
Can experience some problems when using XCMS version < 3 and obiwarp retention time correction.

See Bioconductor documentation for more details, function msPurity::frag4feature()

Outputs

frag4feature_rdata: An updated purityA object saved as rdata file with fragmentation-feature links added
frag4feature_grouped_msms: A flat file of all the XCMS peaks for each grouped feature and the corresponding fragmentation scans
frag4feature_sqlite: An SQLite database of the data (including fragmentation scans)