Assign formulas to theoretical isotope distributions

[rkjulian]

Is there a way to use this package to generate all the formulas that could be assigned to a single m/z value (with an arbitrary intensity - say 100%)? I want to show how many formulas can be generated as a function of mass accuracy. If possible, I'd like to include the isotopes to help narrow the formula list. So far, short lists of m/z, and intensity loaded into a data.frame() and given as input for the peaks parameter of MFAssign() fails and throws errors.

The data frame I am using is:

      mass       prob
1 300.1600 100.000000
2 301.1633  19.630277
3 302.1667   1.819698

Mono_Iso <- IsoFiltR(isotopes_df, SN = 10)
mono <- Mono_Iso[["Mono"]]
iso <- Mono_Iso[["Iso"]]

Gives:
mono

  exp_mass abundance
1   300.16       100

iso

  exp_mass abundance tag
2 301.1633  19.63028 C13

This is for Codeine which is C18 H22 N1 O3

Looking at the code, it seems as if the function ignores everything below 300 m/z by default, so I thought I'd have to set DeNovo to something bigger even to get a peak list for processing in the function.

z <- MFAssign(peaks=mono, ionMode = "pos", DeNovo = 500)

Gives these errors/warnings:

Error in `$<-.data.frame`(`*tmp*`, "mode", value = "pos") : 
  replacement has 1 row, data has 0
In addition: Warning messages:
1: There was 1 warning in `dplyr::filter()`.
ℹ In argument: `CH2_num == min(CH2_num)`.
Caused by warning in `min()`:
! no non-missing arguments to min; returning Inf 
2: There was 1 warning in `dplyr::filter()`.
ℹ In argument: `(CH2_num == (min(CH2_num) + 2))`.
Caused by warning in `min()`:
! no non-missing arguments to min; returning Inf 

I realize that my application is off the normal workflow. I can create a longer simulated spectrum or adjust the input to something closer to a normal application if that would make it more compatible.

Thanks for the help,
Randy