Mercurial > repos > ecology > stoc_mainglm
changeset 1:a961be0a964f draft default tip
"planemo upload for repository https://github.com/Alanamosse/Galaxy-E/tree/stoctool/tools/stoc commit d49a4da1ffac1f33a15fdb7ae98827d0034a7879"
author | ecology |
---|---|
date | Mon, 11 May 2020 17:18:16 -0400 |
parents | df3ce23d0d23 |
children | |
files | FunctTrendSTOCGalaxy.r mainglm.xml stoceps_macros.xml |
diffstat | 3 files changed, 8 insertions(+), 47 deletions(-) [+] |
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--- a/FunctTrendSTOCGalaxy.r Thu Apr 02 03:32:56 2020 -0400 +++ b/FunctTrendSTOCGalaxy.r Mon May 11 17:18:16 2020 -0400 @@ -62,7 +62,7 @@ if(length(colNull)>0){ cat("\n",length(colNull)," Species removed from the analysis, abundance is always 0.\n\n",sep="") #Espèces enlevées de l'analyse car abondance toujours égale a 0\n\n",sep="") #tabNull <- data.frame(Code_espece = colNull, nom_espece = tabsp[colNull,"nom"]) - #cat("\n\n",sep="") + cat("Removed absent species : \n-",paste(colNull,collapse="\n-"),sep="") tab <- tab[,c("carre","annee",colConserve)] } ################################################################################ FIN DE LA PARTIE ISOLABLE @@ -119,7 +119,7 @@ cat("\n",length(colSupr)," Rare species removed from the analysis.\n\n",sep="") #tabSupr <- subset(tabsp,espece %in% colSupr ,select=c("espece","nom")) #tabSupr <- tabSupr[order(tabSupr$espece),] - #cat("\n\n",sep="") + cat("Removed rare species : \n-",paste(colSupr,collapse="\n-"),sep="") } if(length(colConserve)==0) {
--- a/mainglm.xml Thu Apr 02 03:32:56 2020 -0400 +++ b/mainglm.xml Mon May 11 17:18:16 2020 -0400 @@ -1,4 +1,4 @@ -<tool id="stoceps_glm" name="Estimate temporal population evolution" version="@VERSION@"> +<tool id="stoceps_glm" name="Estimate temporal population variation" version="@VERSION@"> <description>by species</description> <macros> <import>stoceps_macros.xml</import> @@ -94,12 +94,12 @@ </tests> <help><![CDATA[ ================================================= -STOC Estimate species population evolution +STOC Estimate species population variation ================================================= **What it does** -Compute and plot evolution of species population, using a glm model. +Compute and plot trends of species population, using a glm model of formula : abundance ~ site + year. Testing the effect of site and year on abundance with quasipoisson distribution. | @@ -142,44 +142,6 @@ UnPublished script available at http://www.vigienature.fr/sites/vigienature/files/atoms/files/analysestoceps_0.zip the first version written by Romain Lorrilliere -Original script information: - -Estimate temporal evolution of population per species - ExeMainGlmGalaxy.r -This script analyse the temporal evolution of species population and create graphical vizualisation. - -Script needs the followings inputs : - - stoc or community data filtered with at least 4 columns: year, site, species, and abundance with 0. Corresponding to "observed" or predicted 0 abundance. May come from the tools "Preprocess population data for evolution trend analyzes" (ExemakeTableAnalyseGalaxy.r) followed by "Filter species with rare and low abundances" (ExeFilteringRareLowabundSPGalaxy.r). - - species details file with name and indicator status file with at least 2 columns: the species name or species ID (found in the community data or in stoc data) and his status as indicator species - - file that stocks functions : "FunctTrendSTOCGalaxy.r" - - -Arguments are : - - spExclude: list of species (using the the species name or ID) that you want to exclude - - assessIC : compute and show confidence interval in plots (TRUE / FALSE) - - analysis custom id - - -How to execute, eg : - # all files are available in github repo - #Exec id=mainglm, return IC on plot, no species excluded - $ Rscript ExeMainGlmGalaxy.r' Datafilteredfortrendanalysis.tabular tabSpecies.csv 'mainglm' '' 'TRUE' FunctTrendSTOCGalaxy.r - - -Outputs are created in an Output repo : -GLM gives 1 graph per species and 2 tables: -- nameofspecies_id.png (one plot per species) -- tendanceGlobalEspece_id.tabular -- variationsAnnuellesEspece_id.tabular - - -R library needed -r-lme4 version 1.1.18.1 -r-ggplot2 version 3.0.0 -r-speedglm version 0.3.2 -r-arm version 1.10.1 -r-reshape version 0.8.8 -r-data.table version 1.12.0 -r-reshape2 version 1.4.3 ]]></help> <expand macro="stoceps_bibref" /> </tool>
--- a/stoceps_macros.xml Thu Apr 02 03:32:56 2020 -0400 +++ b/stoceps_macros.xml Mon May 11 17:18:16 2020 -0400 @@ -1,5 +1,5 @@ <macros> - <token name="@VERSION@">0.0.1</token> + <token name="@VERSION@">0.0.2</token> <xml name="reshape_requirements"> <requirements> <requirement type="package" version="0.8.8">r-reshape</requirement> @@ -53,11 +53,10 @@ <param name="compute_ic" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="yes" label="Compute confidence intervals"/> </xml> <xml name="stoceps_filter_glmmtmb"> - <filter> settings['advanced'] == 'advanced'</filter> - <filter> settings['method'] == 'glmmtmb'</filter> + <filter> method['model'] == 'glmmtmb'</filter> </xml> <xml name="stoceps_filter_gam"> - <filter> settings['method'] == 'gam'</filter> + <filter> method['model'] == 'gam'</filter> </xml> <xml name="stoceps_bibref"> <citations>