Package: QFASA 1.2.1

Connie Stewart

QFASA: Quantitative Fatty Acid Signature Analysis

Accurate estimates of the diets of predators are required in many areas of ecology, but for many species current methods are imprecise, limited to the last meal, and often biased. The diversity of fatty acids and their patterns in organisms, coupled with the narrow limitations on their biosynthesis, properties of digestion in monogastric animals, and the prevalence of large storage reservoirs of lipid in many predators, led to the development of quantitative fatty acid signature analysis (QFASA) to study predator diets.

Authors:Connie Stewart [cre, aut, cph], Sara Iverson [aut, cph], Chris Field [aut], Don Bowen [aut], Wade Blanchard [aut], Shelley Lang [aut], Justin Kamerman [aut], Hongchang Bao [ctb], Holly Steeves [aut], Jennifer McNichol [aut], Tyler Rideout [aut]

QFASA_1.2.1.tar.gz
QFASA_1.2.1.zip(r-4.7)QFASA_1.2.1.zip(r-4.6)QFASA_1.2.1.zip(r-4.5)
QFASA_1.2.1.tgz(r-4.6-x86_64)QFASA_1.2.1.tgz(r-4.6-arm64)QFASA_1.2.1.tgz(r-4.5-x86_64)QFASA_1.2.1.tgz(r-4.5-arm64)
QFASA_1.2.1.tar.gz(r-4.7-arm64)QFASA_1.2.1.tar.gz(r-4.7-x86_64)QFASA_1.2.1.tar.gz(r-4.6-arm64)QFASA_1.2.1.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
QFASA/json (API)

# Install 'QFASA' in R:
install.packages('QFASA', repos = c('https://cstewartgh.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cstewartgh/qfasa/issues

Datasets:
  • bal.diet.data - Sample example of balanced repeatability diet estimates data with only two repeated measurements per predator.
  • CC - Fatty acid calibration coefficients.
  • FAset - List of fatty acids used in sample prey and predator data sets, 'preyFAs' and 'predatorFAs' respectively.
  • predatorFAs - Predator fatty acid signatures. Each predator signature is a row with fatty acid proportions in columns.
  • preyFAs - Prey fatty acid signatures. Each prey signature is a row with fatty acid proportions in columns.
  • unbal.diet.data - Sample example of unbalanced repeatability diet estimates data with a max of two repeated measurements per predator.

On CRAN:

Conda:

4.90 score 1 stars 20 scripts 296 downloads 10 mentions 30 exports 123 dependencies

Last updated from:fe5a5bbccf. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK282
linux-devel-x86_64OK314
source / vignettesOK442
linux-release-arm64OK311
linux-release-x86_64OK313
macos-release-arm64OK191
macos-release-x86_64OK322
macos-oldrel-arm64OK192
macos-oldrel-x86_64OK480
windows-develOK267
windows-releaseOK258
windows-oldrelOK257
wasm-releaseFAIL201

Exports:AIT.distAIT.moreAIT.objbackward.eliminationchisq.CAchisq.distcomp.repconf.methcreate.d.matCS.moreCS.objforward.selectionKL.distKL.moreKL.objMEANmethmultiplicativeReplacementp.MLEp.MUFASAp.QFASAp.sim.QFASAp.SMUFASAPOOLVARmethprey.clusterprey.on.preypseudo.predpseudo.pred.normtestfordiff.ind.boottestfordiff.ind.boot.funtestfordiff.ind.pval

Dependencies:base64encbayesmBHbigassertrbigparallelrbigstatsrbitbootbootstrapbslibcachemclasscliclustercodetoolsCompositionalcompositionscowplotcpp11DEoptimRdigestdoParalleldplyremplikevaluatefarverfastmapffflockfontawesomeforeachformatRfsfutile.loggerfutile.optionsfuturefuture.applygamlssgamlss.datagamlss.distgenericsggplot2glmnetglobalsgluegtablehighrhtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteknitrlabelinglambda.rlatticelifecyclelistenvmagrittrMASSMatrixMatrixModelsmdamemoisemgcvmimeminpack.lmmixturemnormtmvtnormnlmennetnumDerivosqpparallellypermutepillarpkgconfigpsquadprogquantregR6rangenrappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppGSLRcppParallelRfastRfast2rglRhpcBLASctlrlangrmarkdownrmioRnanoflannrobustbaseRsolnpRSpectraS7sassscalesshapesnSparseMsurvivaltensorAtibbletidyselecttinytexTMBtruncnormutf8vctrsveganviridisLitewithrxfunyamlzigg

SMUFASA Workflow Example
Load Packages | Modeling Inputs | Fatty Acid Set | Matrix of Predator FA Signatures | Matrix of Prey FA Signatures | Prey Lipid Content | Running SMUFASA | p.SMUFASA Output | Calibration Coefficient Estimates | Diet Estimates | nll | Var_Epsilon | Obtaining Diet Estimates | QFASA | MUFASA
Rendered fromSMUFASA_Workflow_Example.Rmdusingknitr::rmarkdown

Last update: 2022-10-18
Started: 2021-07-20

Parallel Execution for Confidence Intervals
Set Number of Cores | Create Cluster | Confidence Intervals | Shut Down Cluster | Portability
Rendered fromParallel_Execution_for_Confidence_Intervals.Rmdusingknitr::rmarkdown

Last update: 2022-10-18
Started: 2021-06-02

MUFASA Workflow Example
Load Package | Modeling Inputs | Fatty Acid Set | Matrix of Predator FA Signatures | Matrix of Prey FA Signatures | Prey Lipid Content (Fat Content) | Calibration Coefficients | Running MUFASA | p.MUFASA Output | Diet Estimates | nll | Var_Epsilon
Rendered fromMUFASA_Workflow_Example.Rmdusingknitr::rmarkdown

Last update: 2022-10-18
Started: 2021-06-02

QFASA Workflow Example
Load Package | Modeling Inputs | Distance Measure | Fatty Acid Set | Matrix of Predator FA signatures | Matrix of Prey FA signatures | Prey Lipid Content | Calibration Coefficients | Run QFASA | p.QFASA Output | Diet Estimates | Additional Measures | Note that the function "conf.meth" will return approximate simultaneous confidence intervals for diet.
Rendered fromQFASA_Workflow_Example.Rmdusingknitr::rmarkdown

Last update: 2021-07-20
Started: 2021-06-02

Readme and manuals

Help Manual

Help pageTopics
Returns the distance between two compositional vectors using Aitchison's distance measure.AIT.dist
Used to provide additional information on various model components evaluated at the optimal solution, i.e., using the QFASA diet estimates and Aitchison distance measure.AIT.more
Used in 'solnp()' as the objective function to be minimized when Aitchison distance measure is chosen.AIT.obj
Returns diet estimates corresponding to a sample of predators based on a backward elimination algorithm that chooses the prey species to be included in the modelling.backward.elimination
Sample example of balanced repeatability diet estimates data with only two repeated measurements per predator.bal.diet.data
Fatty acid calibration coefficients.CC
Called by 'create.d.mat()' to compute the chi-square distance.chisq.CA
Returns the distance between two compositional vectors using the chi-square distance.chisq.dist
Repeatability in Diet Estimatescomp.rep
Confidence Intervals for Diet Proportionsconf.meth
Called by 'testfordiff.ind.boot.fun()' to create a matrix of distances.create.d.mat
Used to provide additional information on various model components evaluated at the optimal solution, i.e., using the QFASA diet estimates and chi-square distance measure.CS.more
Used in 'solnp()' as the objective function to be minimized when chi-square distance measure is chosen. Unlike 'AIT.obj()' and 'KL.obj()', does not require modifying zeros.CS.obj
List of fatty acids used in sample prey and predator data sets, 'preyFAs' and 'predatorFAs' respectively.FAset
Returns diet estimates corresponding to a sample of predators based on a forward selection algorithm that chooses the prey species to be included in the modelling.forward.selection
Returns the distance between two compositional vectors using Kullback-Leibler distance measure.KL.dist
Used to provide additional information on various model components evaluated at the optimal solution, i.e., using the QFASA diet estimates and Kullback-Leibler distance measure.KL.more
Used in 'solnp()' as the objective function to be minimized when Kullback-Leibler distance measure is chosen.KL.obj
Returns the geometric mean of a compositional vectormean_geometric
Returns the multivariate mean FA signature of each prey group entered into the QFASA model. Result can be passed to prey.mat in 'p.QFASA()'.MEANmeth
Multiplicative replacement of zeroesmultiplicativeReplacement
Returns simplified MLE diet estimates corresponding to a sample of predators.p.MLE
Returns MUFASA diet estimates corresponding to a sample of predators.p.MUFASA
Returns QFASA diet estimates corresponding to a sample of predators.p.QFASA
Simultaneous estimation of diet composition and calibration coefficientsp.sim.QFASA
Simultaneous maximum unified fatty acid signature analysisp.SMUFASA
Computes within species variance-covariance matrices on transformed scaled, along with a pooled estimate.POOLVARmeth
Predator fatty acid signatures. Each predator signature is a row with fatty acid proportions in columns.predatorFAs
Produces a dendrogram using distances between the mean FA signatures of the prey types.prey.cluster
Each prey fatty acid signature is systematically removed from the supplied prey database and its QFASA diet estimate is obtained by treating the individual as a predator.prey.on.prey
Prey fatty acid signatures. Each prey signature is a row with fatty acid proportions in columns.preyFAs
Generate a pseudo predator by sampling with replacement from prey database.pseudo.pred
Generate a pseudo predator parametrically from multivariate normal distributions.pseudo.pred.norm
QFASA: A package for Quantitative Fatty Acid Signature AnalysisQFASA-package QFASA
Returns 'sum(alpha)' and used in 'solnp()'.QFASA.const.eqn
Splits prey database into a simulation set (1/3) and a modelling set (2/3). Returns a list:split_prey
Called by 'testfordiff.ind.pval()'.testfordiff.ind.boot
Called by 'testfordiff.ind.boot()'.testfordiff.ind.boot.fun
Test for a difference between two independent samples of compositional data. Zeros of any type are allowed.testfordiff.ind.pval
Sample example of unbalanced repeatability diet estimates data with a max of two repeated measurements per predator.unbal.diet.data