Description Usage Arguments Value Examples
View source: R/build_gaussians.R
Identify peaks in cofractionation profiles by deconvolving peaks in Gaussian mixture models. Models are mixtures of between 1 and 5 Gaussians. Profiles are preprocessed prior to building Gaussians by filtering and cleaning. By default, profiles with fewer than 5 nonmissing points, or fewer than 5 consecutive points after imputation of single missing values, are removed. Profiles are cleaned by replacing missing values with nearzero noise, imputing single missing values as the mean of neighboring points, and smoothing with a moving average filter.
1 2 3 4 5 6 7  build_gaussians(profile_matrix, min_points = 1, min_consecutive = 5,
impute_NA = TRUE, smooth = TRUE, smooth_width = 4,
max_gaussians = 5, criterion = c("AICc", "AIC", "BIC"),
max_iterations = 50, min_R_squared = 0.5, method = c("guess",
"random"), filter_gaussians_center = TRUE,
filter_gaussians_height = 0.15, filter_gaussians_variance_min = 0.5,
filter_gaussians_variance_max = 50)

profile_matrix 
a numeric matrix of coelution profiles, with proteins
in rows, or a 
min_points 
filter profiles without at least this many total,
nonmissing points; passed to 
min_consecutive 
filter profiles without at least this many
consecutive, nonmissing points; passed to 
impute_NA 
if true, impute single missing values with the average of
neighboring values; passed to 
smooth 
if true, smooth the chromatogram with a moving average filter;
passed to 
smooth_width 
width of the moving average filter, in fractions;
passed to 
max_gaussians 
the maximum number of Gaussians to fit; defaults to 5.
Note that Gaussian mixtures with more parameters than observed (i.e.,
nonzero or NA) points will not be fit. Passed to

criterion 
the criterion to use for model selection;
one of "AICc" (corrected AIC, and default), "AIC", or "BIC". Passed to

max_iterations 
the number of times to try fitting the curve with
different initial conditions; defaults to 50. Passed to

min_R_squared 
the minimum Rsquared value to accept when fitting the
curve with different initial conditions; defaults to 0.5. Passed to

method 
the method used to select the initial conditions for
nonlinear least squares optimization (one of "guess" or "random");
see 
filter_gaussians_center 
true or false: filter Gaussians whose centres
fall outside the bounds of the chromatogram. Passed to

filter_gaussians_height 
Gaussians whose heights are below this
fraction of the chromatogram height will be filtered. Setting this value to
zero disables heightbased filtering of fit Gaussians. Passed to

filter_gaussians_variance_min 
Gaussians whose variance falls below
this number of fractions will be filtered. Setting this value to
zero disables filtering. Passed to

filter_gaussians_variance_max 
Gaussians whose variance is above
this number of fractions will be filtered. Setting this value to
zero disables filtering. Passed to

a list of fit Gaussian mixture models, where each item in the list contains the following five fields: the number of Gaussians used to fit the curve; the R^2 of the fit; the number of iterations used to fit the curve with different initial conditions; the coefficients of the fit model; and the curve predicted by the fit model. Profiles that could not be fit by a Gaussian mixture model above the minimum Rsquared cutoff will be absent from the returned list.
1 2 3  data(scott)
mat < clean_profiles(scott[seq_len(5), ])
gauss < build_gaussians(mat, max_gaussians = 3)

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