Description Usage Arguments Details Value Examples
Returns identifying information for the compounds in the order in which the corresponding regression coefficient for a given compound first becomes nonzero as part of the Elastic Net path
1 2 |
msObj |
An object of class |
bioact |
Either a numeric vector or matrix, or a data frame providing bioactivity data. If a numeric vector, then it is assumed that each entry corresponds to a particular fraction. If the data is 2-dimensional, then it is assumed that each column corresponds to a particular fraction, and that each row corresponds to a particular bioactivity replicate. |
region_ms |
Either |
region_bio |
Either |
lambda |
A single nonnegative numeric value providing the quadratic penalty mixture parameter argument for the elastic net model. The elastic net fits the least squares model with penalty function γ|β|_1 + λ|β|^2 where β is the vector
of regression coefficients and γ, λ ≥ 0.
|
pos_only |
Either |
ncomp |
Either |
rankEN
prepares the data by extracting the region of interest
from the mass spectrometry abundance data and from the bioactivity data.
If bioactivity replicates are present, then the within-fraction
replicates are averaged. Once the data has been converted into the
appropriate form, then an elastic net model is fitted by invoking the
enet
function from the elasticnet
package, and an ordered
list of candidate compounds is constructed such that compounds are ranked
by the order in which they first enter the model. The list may be
filtered and / or pruned before being returned to the user, as determined
by the arguments to pos_only
and ncomp
.
Returns an object of class rankEN
. This object is a
list
with elements described below. The class is equipped with a
print
, summary
, and extract_ranked
function.
mtoz
A vector providing the mass-to-charge values of the
candidate compounds, such that the k
-th element of the vector
provides the mass-to-charge value of the k
-th compound to
enter the elastic net model, possibly after removing compounds
nonpositively correlated with bioactivity levels.
charge
A vector providing the charge state of the
candidate compounds, such that the k
-th element of the vector
provides the charge state of the k
-th compound to enter the
elastic net model, possibly after removing compounds nonpositively
correlated with bioactivity levels.
comp_cor
A vector providing the correlation between each
of the candidate compounds and the bioactivity levels, such that the
k
-th element of the vector provides the correlation between
the k
-th compound to enter the elastic net model and the
bioactivity levels, possibly after removing compounds nonpositively
correlated with bioactivity levels.
enet_fit
The fitted model object produced by
rankEN
's internal invokation of the enet
function from
the elasticnet
package.
summ_info
A list containing information related to the data used to fit the elastic net model; used by the summary function.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | # Load mass spectrometry data
data(mass_spec)
# Convert mass_spec from a data.frame to an msDat object
ms <- msDat(mass_spec = mass_spec,
mtoz = "m/z",
charge = "Charge",
ms_inten = c(paste0("_", 11:43), "_47"))
# Load growth inhibition bioactivity data. Each element in bioact is a
# stand-alone dataset for a species of virus or bacteria.
data(bioact)
# Perform the candidate ranking procedure with fractions 21-24 as the region
# of interest. Note that it is not advisable to calculate the elastic net
# estimates with 30,799 candidate compounds on 4 data points!
## Not run:
rank_out <- rankEN(msObj = ms,
bioact = bioact$ec,
region_ms = paste0("_", 21:24),
region_bio = paste0("_", 21:24),
lambda = 0.001,
pos_only = TRUE,
ncomp = NULL)
# print, summary function
rank_out
summary(rank_out)
# Extract ranked compounds as a data.frame
ranked_candidates <- extract_ranked(rank_out)
## End(Not run)
|
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