Difference between revisions of "Pk nextGen"

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(Multiple Dimensions)
(Multiple Dimensions)
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MJC: Unfortunately, there are TW applications which will require fitting in two more dimensions than the current AMS-runs... some will want averaging, some will not. As per the m/z calibration, a mask system is going to be required to build up the averaging domains. This is not actually that heinous to put into place and, if we use a MSConcs-esque approach (or even MSConcs itself), the user could specify ANY dimensional base for averaging. The example above would be easily incorporated. But in summary, 3-D fitting is going to be a pre-requisite, along with all the hideous user interface issues this will present afterwards. But the AMS panel need not worry about that! But PTOF data will be able to be fit with the TW scheme...
 
MJC: Unfortunately, there are TW applications which will require fitting in two more dimensions than the current AMS-runs... some will want averaging, some will not. As per the m/z calibration, a mask system is going to be required to build up the averaging domains. This is not actually that heinous to put into place and, if we use a MSConcs-esque approach (or even MSConcs itself), the user could specify ANY dimensional base for averaging. The example above would be easily incorporated. But in summary, 3-D fitting is going to be a pre-requisite, along with all the hideous user interface issues this will present afterwards. But the AMS panel need not worry about that! But PTOF data will be able to be fit with the TW scheme...
  
MJC: '''THIS IS THE POINT OF IMMEDIATE CONCERN'''. The first step in the PIKA-process (see map below) is to generate the raw MS less baseline... at this point, for multi-dimensional data, the integration and axis-bases (eg t_series for 1-D AMS data) need to be considered. I know JDA has always contended not to integrate mass spectra before fitting, but is this realistic in a low S:N environment? It is clear that '''MSConcs can generate integrated raw MS''' (and the baselines) very easily, and I would like to take advantage of this capability. BUT! MSConcs also pulls everything into memory at once... so a separate function that calls the same mapping procedures might actually be required. :(
+
MJC: '''THIS IS THE POINT OF IMMEDIATE CONCERN'''. The first step in the PIKA-process (see map below) is to generate the raw MS less baseline... at this point, for multi-dimensional data, the integration and axis-bases (eg t_series for 1-D AMS data) need to be considered. I know JDA has always contended not to integrate mass spectra before fitting, but is this realistic in a low S:N environment? It is clear that '''MSConcs can generate integrated raw MS''' (and the baselines) very easily, and I would like to take advantage of this capability. BUT! MSConcs also pulls everything into memory at once... it might be that the solution here is to append to Concs such that it has the capability to write to HDF. Looking at the code, this does not seem very hard. James, what do u think?
  
 
===DTS: Proposed step forward===
 
===DTS: Proposed step forward===

Revision as of 04:52, 21 September 2010

Discussion: Next-generation PIKA

What we know for sure:

1. MikeC is to develop a PIKA-esque tool for multi-dimensional data from TofDAQ data files.
2. The non-AMS data format and multi-dimensional aware criteria forces a re-write of the HR code rather than straight adoption of existing PIKA
3. Other TW (non-AMS) applications will wish to use many existing PIKA features (not limited to PWPS, HRfrag, families, isotopic constraints), but others will be less applicable (obviously, the AMS-centric parts!).
4. Whatever gets written should address existing desires and concerns with the PIKA code, and be fully transparent so as to accept any input data type. It should be developed with memory and speed optimisation in mind.

What Mike initially proposed:

  • An ion indexing scheme to allow saving/comparison of different ion fits at a given unit mass
  • A dimension in the HR data set to save multiple copies of HR fits (this could be for different calibration, PW, PS, or simply open/closed AMS data)
  • Fitting of subsets of unit masses within the mass spectrum (but over any dimensionality in time) to speed the process.

Concerns and discussion

Isotopic constraining

DTS: If users want to constrain isotopic species (generally a very fair and sensible thing to do) than the order of the set of HR ions to fit at any m/z matters. For example if a user only wants to fit 3 HR ions at m/z x, but one of these ions is an isotope, then one has to fit the isotopic parent at m/z y, etc. It could be argued that most isotopic abundances are very small; we could gain greater flexibility in allowing any order, any subset of HR ions to be fit at the cost of not fitting or not constraining isotopic ions.

MJC: Agreed, this is a difficult issue to work around with the proposed system, one that I had not considered. I would argue that:
1. Isotopic constraints need to be an inherent feature included in the software,
2. The HR sticks are, in general, sensitive to using these constraints, and
3. Building a scheme where you just fit the required ions to generate a result for a given m/z is both complicated and prone to error.

MJC: Thus, I only see two solutions:
1. The existing format where we pull the whole MS into memory and fit all the masses sequentially according to the isotopic constraints.
2. A fully-unconstrained format using the ion-indexing scheme.
Clearly, (1) could also use an ion-indexing scheme, however. At this point, I propose we need to keep to the exising format.

Multiple fitting schemes

DTS: The philosophy so far in all our AMS code is that there is *one* version of any data set, i.e. MSSDiff_p. The proposed scheme would allow several versions of the HR stick for any given ion => possible confusion.

DTS: For example, we do not have a copy of MSSDiff_p for one set of m/z calibration parameters and another copy for a different set of m/z parameters (ditto for single ion values, baseline settings etc). This is beneficial in that the experiments don’t get monstrously big with each and every calculation of sticks and, most importantly, the user isn’t confused by having to select from a variety previously made versions – there is one and only one version of MSSOpen sticks available to the user.

MJC: In response, I point out that we MUST include this capability, purely to retain the ability to deal with open/closed/diff spectra. This is the most obvious example of multiple sets of fits for any given point in (clock) time. Whether the information is stored as an extra dimension with appropriate labelling, or a different wave, is in the details.

MJC: I was envisaging a system whereby the user would save a "HR-setup" profile before calculating the fits. This would be advantageous even in the instance of NOT allowing multiple fitting results to be saved, as one could probe results without having to recalculate the PW PS parameters etc. So long as this information was stored appropriately, and given as a drop-down menu (or likewise), I would contend the confusion would be minimised. And of course, overwriting is an easy option to include.  ???

Ion 'bit' indexing

DTS: Possible confusion by the user of different ‘naming’ schemes. I.e. CH2NO+ is the same fragment as CHNHO+. The mass calculator code added in the latest version 1.09 can help users calculate exact mass values and identify possible HR ion naming duplication. Also, in Mike’s proposed scheme, a user would never eliminate (completely remove) an HR ion -it is only an additive process. Perhaps this is workable, but in general users will always want the ability to remove something. If the mass of the HR ion (not the name) is the identifying feature, this may not be an issue, as long as we have enough digits of precision.

MJC: Under the proposed naming scheme, the exact mass AND name were going to be saved in the ion index (text) wave. From your point above it seems clear this would also need a duplication tool to aid finding duplicate ions... by using a text wave I was hoping to avoid the problem of digits-of-precision, for one can make the number as long as you like!

DTS: In your scenario, if the user requests a simple time series of C2H3O, the user will have to specify which HR fitting setting to use: fit 3 or 2 HR ions at 43. The same decision would have to be made at potentially every nominal m/z etc etc

MJC: This is a potential pitfall. I guess I envisaged this setup such that multiple fit instances FOR ONE UNIT MASS could be displayed in the "single-MS_analysis" step, which is not currently easy to do. I argue that this is a feature we should work to include somehow.

MJC: The principle of an indexing scheme of some kind should be included... the ability of the code to be indifferent to the order of ions in the saved dataset means that the user can pull in any exact-mass-list they like, at any time, and the dataset will not be affected. This is potentially important given the different applications that this code will need to be able to analyse... the ion lists are surely not going to remain equivalent?

MJC: Thus, the question is how to avoid the clear problem with this approach Donna has highlighted above. I would thus propose that any step that deals with multiple instances of ion fits for a given unit mass should be required to be finalised before time-series fitting. ie. the HDF-dataset does NOT contain multiple ion instances (other than open/closed etc).

Multiple Dimensions

DTS: The need to add/average PToF raw spectra before HR fits. For AMS PToF data, the signal is so low that I anticipate a grouping/averaging (the AMS size and/or time dimension) is needed of raw spectra before HR fits are attempted. This presents it’s own indexing challenge. For AMS PToF data, one can imagine wanting to average the raw spectra for bins representing 30-100, 100-300, 300-1000nm, for one run before performing the HR fits. (In general it is better to examine the HR fits of an PToF bin-averaged spectra than average the HR fits of noisy raw PToF spectra.) I imagine a similar scenario is true for other Tofwerk ms applications.

MJC: Unfortunately, there are TW applications which will require fitting in two more dimensions than the current AMS-runs... some will want averaging, some will not. As per the m/z calibration, a mask system is going to be required to build up the averaging domains. This is not actually that heinous to put into place and, if we use a MSConcs-esque approach (or even MSConcs itself), the user could specify ANY dimensional base for averaging. The example above would be easily incorporated. But in summary, 3-D fitting is going to be a pre-requisite, along with all the hideous user interface issues this will present afterwards. But the AMS panel need not worry about that! But PTOF data will be able to be fit with the TW scheme...

MJC: THIS IS THE POINT OF IMMEDIATE CONCERN. The first step in the PIKA-process (see map below) is to generate the raw MS less baseline... at this point, for multi-dimensional data, the integration and axis-bases (eg t_series for 1-D AMS data) need to be considered. I know JDA has always contended not to integrate mass spectra before fitting, but is this realistic in a low S:N environment? It is clear that MSConcs can generate integrated raw MS (and the baselines) very easily, and I would like to take advantage of this capability. BUT! MSConcs also pulls everything into memory at once... it might be that the solution here is to append to Concs such that it has the capability to write to HDF. Looking at the code, this does not seem very hard. James, what do u think?

DTS: Proposed step forward

A small step forward: ?? Perhaps we can tweak the existing HR code with a modified version of your proposal. Suppose the user really want to get diagnostic information for all runs about whether to fit CHNO;C3H5O;C3H7; or to leave CHNO out. (leaving aside for the moment any isotope constraining issues). Perhaps the code could generate two data sets: HRSticks43_7 and HRSticks43_6. In the AMS world, both data sets would contain at least 3 columns. Version “7” would contain 3 nonzero columns and version “6” 2 nonzero columns. We could id the columns using the HR ion bit-wise idea you have so that column 0 is always CHNO;column 1 is always C3H5O, etc. So the ‘7’ and ‘6’ suffix in the data set name identifies the HR ions fit. This way, a user could examine these multiple versions of HR ions fit at 43.

PIKA fitting process: steps

2010-09-21 MJC PIKAconceptmap.jpg

1. Preparation for HR fitting

The order of preparatory steps below is generally not modifiable. (MJC: comments added for changes required in the TW version)

(1A) Get good m/z calibration parameters. Mike has this code in place for Tofwerk files.

(1B) Get good baseline-removed spectra.
The purpose of saving copies of the raw spectra with the baseline removed is so that the multipeak fitting is done on the ‘same’ spectra. This insures that the calculation of any baseline isn’t dependent on settings (‘resolution’ interpolations parameters) that could be adjusted by the user and then not saved, not recorded, an hence not replicable.
MJC: Something to consider: should the dimensional averaging be performed at this stage? This would limit the user to the prescribed dimensional bases, but facilitate the sped-up analysis currently available in PIKA.??

(1C) Get good peak width (PW), peak shape (PS).
Getting good values for these parameters is necessarily an iterative process. In general one looks at 100s of sets of isolated HR ions (i.e. C4H9+, etc ) spectra to get good statistics for PW and PS. Once a user is confident that selected HR ions are behaving in a consistent and ‘smooth’ manner, one can set the PW and even PS on an individual run basis if needed.
MJC: TW product will require a more generalised version of the current code, which hard-wires in AMS-specific ions...

(1D) Select the HR ions to fit.
This is highly variable depending on the application. Similar to Mike’s m/z calibration routine, I envision a simple interface whereby a user imports settings appropriate to their type of application.
MJC: Since the UM now I'm wondering about de-constraining the list, too.... hmmm

(1E) Select a subset of HR ions in (1D) to be constrained.
Constrained means that the fitting routine does not ‘fit’ this HR ion – the peak height is fixed to a value based on the magnitude of the HR ion’s isotopic ‘parent’ that has been previously fit or determined. This has consequences about the order in which UMR sets of HR ions at on m/z are fit.

2. Perform HR fitting

In the current AMS HR code the HR fitting is performed at one UMR set of HR ions (all chosen HR ions at an individual integer m/z range). For example at nominal m/z 18 the HR ions 18O+, H2O+, 15NH3 at 17.999161, 18.010559, 18.023581 are fit in one ‘set’. Typically isotopic HR ions are constrained, and hence in this case the magnitude of the HR ions of O+ and NH3+ would need to be determined from sets of HR ions at nominal m/z at 16 and 17 before the set of HR ions at 18 would be found. In future applications ToF mass spec applications of high organic fragments (>250m/zish?) with a positive mass defect the division into nominal m/z sets of HR ions could be problematic.

(2A) Single MS high-resolution stick calculation & diagnostics

Before a user spends a lot of computation time generating HR sticks, it is beneficial to examine HR fits of few raw spectra at periods of various concentrations and compositions. This involves visually inspecting each UMR m/z region of interest and significant signal. This visual inspection gives a user feedback on all the parameters that go into the fit: m/z calibration, baseline settings, PW, PS, selection of HR ions to fit. It is often at this stage where at least one of the input parameters of the HR fit requires fine-tuning. Other diagnostics for single spectra include:

  • Comparison of HR summed to UMR vs. UMR sticks.
  • Residuals from the HR fits.
  • “5-panel” graph... Some sort of UMR, family summarized spectra plots. This is more important for EI than for soft or other ionization techniques.
  • Tabulated results. Having easy access to the HR sticks in a table is useful for those wishing to check the math or perform their own subsequent calculations.
  • Mike’s HR ion sensitivity tool.

(2B) High-resolution stick calculation for many spectra

As the AMS HR code currently exists in version 1.09, the HR fitting results are only saved in intermediate files for future access via subsequent ‘fetch’ commands. It is beneficial for users to have a place to ‘play’ while keeping the HR fitting results from being modified.

3. Organizing, displaying HR stick results & diagnostics

(3A) Organization (order of steps important here)

(3Ai) Define HR families
It will always be convenient to group HR ions into families. A family can be defined explicitly by listing its members (i.e. family Cx =C+, C2+, C3+, etc) or by an algorithm that parses the chemical formula of each HR ion. The AMS HR code currently wants families to be determined at the same time as the selection of the HR ions to fit. However, this is unnecessary and future versions will allow more flexibility.

(3Aii) Define HR batch entities
In AMS parlance a batch entity is typically a species, like organics, nitrate, etc. While the grouping of HR ions into families is convenient, it will always be the case that the chemical information a user desires may require a mathematical or specialized treatment of the HR fit results beyond the simply family sorting mechanism. A common AMS example is the parsing of the OH+ signal between the water and the organic species. Every HR species is defined first by two items: (a) a list of families and (b) a frag wave which identifies any modifications based on individual HR ions (such as the OH example above).

(3Aiii) Define HR frag entries
HR frag entries explicitly states the mathematical treatment of any/all specialized considerations of HR ion, whether the HR ion was fit or not.

(3B) Display

Users will require typical output: time series, mass spectra summed or averaged in user-defined ways, and plotted in a variety of formats. What is different from a UMR analysis is that user have an additional type of entity: HR families as well as individual HR ions, unit resolution summed values, and HR species.

(3C) Diagnostics

All the diagnostics outlined in 2A above, and with a time (or other) dimension will be required by users.