Fit dose-response curves

Fit dose-response curves

Usage

fitCurve(
  spec,
  unit = c("M", "mM", "uM", "nM", "pM", "fM"),
  varFilterMethod = c("mean", "median", "q25", "q75", "none"),
  monoisotopicFilter = FALSE,
  averageMethod = c("mean", "median", "sum"),
  normMz = NULL,
  normTol = 0.1,
  alignTol = 0.01,
  binTol = 2e-04,
  SNR = 3,
  halfWindowSize = 3,
  allowNoMatches = TRUE,
  normMeth = c("mz", "TIC", "PQN", "median", "none"),
  SinglePointRecal = TRUE,
  verbose = TRUE
)

Arguments

spec

List of MALDIquant::MassSpectrum

unit

Character, unit of concentration. Used to calculate the concentration in Moles so that pIC50 is correct. Set to "M" if you dont want changes in your concentrations.

varFilterMethod

Character, function applied for high variance filtering. One of the following options mean (default), median, q25, q75 or none (no filtering).

monoisotopicFilter

Logical, filter peaks and just use monoisotopic peaks for curve fit.

averageMethod

Character, aggregation method for average mass spectra ("mean" or "median")

normMz

Numeric, mz used for normalization AND for single point recalibration.

normTol

Numeric, tolerance in Dalton to match normMz

alignTol

Numeric, tolerance for spectral alignment in Dalton.

binTol

Numeric, tolerance for binning of peaks.

SNR

Numeric, signal to noise ratio for peak detection.

halfWindowSize

2ction. See MALDIquant::detectPeaks().

allowNoMatches

Logical, if normMz can not be found in a spectrum, proceed and exclude spectrum or stop

normMeth

Character, normalization method. Can either be "TIC", "PQM", "median" or "mz". If "mz" then the normMz is used. If none no normalization is done.

SinglePointRecal

Logical, perform single point recalibration to normMz

verbose

Logical, print logs to console.

Value

Object of class MALDIassay. The most important slot is fits which contains the IC50 curve fits.

Examples

data(Blank2022spec)

fitCurve(spec = Blank2022spec,
         SinglePointRecal = TRUE, 
         normMz = 760.585, 
         alignTol = 0.1, 
         normTol = 0.1,
         varFilterMethod = "mean") 
#> found mz 760.585 in 32 / 32 spectra
#> 13:36 mzshift was -0.0796625 in mean and 0.0828  abs. max.
#> 13:36 normalizing... 
#> 13:36 aligning spectra... 
#> 13:36 calculating mean spectra... 
#> 13:36 building intensity matrix and applying variance filter... 
#>       Found 216 peaks in total.
#> 13:36 fitting curves... 
#>       Found 23 peaks with high variance using `mean` method.
#> fitting 406.775 (1/23)
#> fitting 406.914 (2/23)
#> fitting 407.933 (3/23)
#> fitting 408.897 (4/23)
#> fitting 409.006 (5/23)
#> fitting 409.96 (6/23)
#> fitting 412.753 (7/23)
#> fitting 412.906 (8/23)
#> fitting 422.889 (9/23)
#> fitting 423.933 (10/23)
#> fitting 424.746 (11/23)
#> fitting 424.903 (12/23)
#> fitting 425.784 (13/23)
#> fitting 425.836 (14/23)
#> fitting 425.913 (15/23)
#> fitting 427.873 (16/23)
#> fitting 428.004 (17/23)
#> fitting 428.848 (18/23)
#> fitting 428.971 (19/23)
#> fitting 437.903 (20/23)
#> fitting 438.04 (21/23)
#> fitting 438.891 (22/23)
#> fitting 439.042 (23/23)
#> 13:36 Done! 
#> ------MALDIassay object------
#> 
#> Including 8 concentrations,
#> ranging from 0 to 30 .
#> Normalization on m/z 760.58 ± 0.1 Da.
#> 
#> Single point recalibation on 760.58 with 0.1 Da tolerance.
#> Avg. mass shift before recal.: -0.0797 Da. Max abs. shift: 0.0828 Da.
#> Avg. mass shift after recal. : -0.0126 Da. Max abs. shift: 0.0126 Da.
#> 
#> Found 216 peaks (SNR 3) and 23 high variance peaks
#> using variance filtering method: mean.
#> 
#> Top5-features based on Fold-Change and R²:
#>        mz mzIdx pEC50   R2 log2FC SSMD   V'    Z'  CRS
#> 1 832.601    22 -0.66 0.99   4.18 4.33 0.98  0.14 75.3
#> 2 810.623    19 -0.54 1.00   1.49 5.04 0.91  0.27 67.3
#> 3 811.624    20 -0.58 1.00   1.59 4.67 0.90  0.22 64.9
#> 4 804.556    18 -0.72 0.99   1.81 3.97 0.83  0.08 56.2
#> 5 835.677    23 -0.95 0.99   1.24 3.66 0.79 -0.02 40.9