Zero hour - Start:

- Write a mock-CWT function in matlab that provides the same results as the wCoefficents as the cwt() method in R.
*(done)* - Write mock getRidge() and identifyMajorPeaks() functions in matlab as a transitional test for the final functions in R
- Make a video explaining, in layman's terms, how the MassSpecWavelet package actually works.

Week 1-2:

- Start developing multiple re-sampling algorithms (wavestrapping, bootstrapping the raw data, and re-sampling the Fourier space) . --Will probably be done in matlab, as I'm more familiar with it than R. This will start with a literature review.
- Perform threshold analysis on each algorithm with a small dataset (probably just the MSexample)
- Collect MS and NMR data. (the CAMDA data set and I also may have a access to MS QC data from a nearby toxicology lab.)

Week 3-4:

- Work out bugs from the re-sampling algorithms and write test functions (which will probably be done in R).
- Extend the testing parameters to the larger dataset to find the particular re-sampling algorithm that works best.
- Perform similar re-sampling analysis on NMR data. --this should be trivial with the algorithms already made sound by the MS data.

Week 5-6:

- Port/convert re-sampling algorithm(s) to R and test again (if not done already).
- Start development of a modified identifyMajorPeaks() method to cover overlapping peaks.
- Start on extending the current methods to NMR (or see what Michael needs done).

Week 7-8:

- Test the modified identifyMajorPeaks() method extensively.
- Continue working on NMR data methods.

Week 9-Deadline:

- Do last touch-ups on whatever is needed and convert algorithms to R if not already done. (quality focused)
- Combine re-sampling, overlapping peaks and NMR work to Michael's project (can be done independently with each completion as well).