Galaxy |

Changeset 12:ddaf84e15d06 (2018-11-08)

Previous changeset 11:ddcc33ff3205 (2018-09-05) Next changeset 13:2ae2d26e3270 (2018-12-12)

Commit message:
planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 6775c83b89d9d903c81a2229cdc200fc93538dfe-dirty

modified:
w4mcorcov.xml
w4mcorcov_calc.R

diff -r ddcc33ff3205 -r ddaf84e15d06 w4mcorcov.xml
--- a/w4mcorcov.xml Wed Sep 05 22:31:21 2018 -0400
+++ b/w4mcorcov.xml Thu Nov 08 23:06:09 2018 -0500

[

b'@@ -1,4 +1,4 @@\n-\xef\xbb\xbf<tool id="w4mcorcov" name="OPLS-DA_Contrasts" version="0.98.15">\n+\xef\xbb\xbf<tool id="w4mcorcov" name="OPLS-DA_Contrasts" version="0.98.16">\n <description>OPLS-DA Contrasts of Univariate Results</description>\n <macros>\n <xml name="paramPairSigFeatOnly">\n@@ -201,13 +201,13 @@\n <has_text text="level1Level2Sig" />\n \n <has_text text="M349.2383T700" />\n- <has_text text="-0.3704185" />\n+ <has_text text="-0.462909875" />\n <has_text text="-36.6668927" />\n <has_text text="0.4914638" />\n <has_text text="0.01302117" />\n \n <has_text text="M207.9308T206" />\n- <has_text text="0.3235022" />\n+ <has_text text="0.504885262" />\n <has_text text="5.97529097" />\n <has_text text="0.207196379" />\n <has_text text="0.04438632" />\n@@ -259,7 +259,7 @@\n <has_text text="level1Level2Sig" />\n \n <has_text text="M200.005T296" />\n- <has_text text="-0.24533821" />\n+ <has_text text="-0.28035717" />\n <has_text text="-3.3573953" />\n <has_text text="0.1157346" />\n <has_text text="0.0647860" />\n@@ -309,13 +309,13 @@\n <has_text text="vip4o" />\n \n <has_text text="M349.2383T700" />\n- <has_text text="-0.37867079" />\n+ <has_text text="-0.4732226665" />\n <has_text text="-37.71066" />\n <has_text text="0.5246766" />\n <has_text text="0.0103341" />\n \n <has_text text="M207.9308T206" />\n- <has_text text="0.31570433" />\n+ <has_text text="0.4927151212" />\n <has_text text="5.86655640" />\n <has_text text="0.2111623" />\n <has_text text="0.0488654" />\n@@ -368,7 +368,7 @@\n <has_text text="NM516T251" />\n <has_text text="flower_yes" />\n <has_text text="other" />\n- <has_text text="0.03402807" />\n+ <has_text text="0.3499550705" />\n <has_text text="0.03526926" />\n <has_text text="0.43664386" />\n <has_text text="0.587701897" />\n@@ -419,13 +419,13 @@\n <has_text text="vip4o" />\n \n <has_text text="M349.2383T700" />\n- <has_text text="0.43361563" />\n+ <has_text text="0.61594030" />\n <has_text text="37.76875778" />\n <has_text text="0.54672558" />\n <has_text text="0.3920409" />\n \n <has_text text="M207.9308T206" />\n- <has_text text="-0.3365475" />\n+ <has_text text="-0.89716403" />\n <has_text text="-6.337903" />\n <has_text text="0.270297" />\n <has_text text="0.037661" />\n@@ -454,14 +454,14 @@\n <has_text text="vip4o" />\n \n <has_text text="M349.2383T700" />\n- <has_text text="-0.0435663" />\n- <has_text text="-1.9068114" />\n- <has_text text="0.0304592" />\n- <has_text text="0.104748883" />\n+ <has_text text="-0.331230562" />\n+ <has_text text="-2.47167915" />\n+ <has_text text="0.0892595" />\n+ <has_text text="0.0049228872" />\n </assert_contents>\n </output>\n </test>\n- \n+ \n <test>\n <param name="dataMatrix_in" value="input_dataMatrix.tsv"/>\n <param name="sampleMetadata_in" value="issue8_input_sampleMetadata.tsv"/>\n@@ -495,6 +495,7 @@\n \n **Author** - Arthur Eschenlauer (University of Minnesota, esch0041@umn.edu)\n \n+**Release Notes** - https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper#release-notes\n \n Motivation\n ----------\n@@ -616,9 +617,13 @@\n |\n \n [OUT] Contrast-detail output PDF\n- | S'..b'n contrast, there is a linear relationship between \'loadp\' and \'correlation\'.\n+- **covariance** - relative covariance of the features projection explaining the difference between the features, < 0 when intensity for level 1 is greater (from formula in *ibid.*, but scaled so that the greatest value has a magnitude of 1)\n - **vip4p** - "variable importance in projection" to the predictive projection, VIP\\ :subscript:`4,p` (Galindo-Prieto *op. cit.*)\n - **vip4o** - "variable importance in projection" to the orthogonal projection, VIP\\ :subscript:`4,o` (*ibid.*)\n - **loadp** - variable loading for the predictive projection (Wiklund *op. cit.*)\n - **loado** - variable loading for the orthogonal projection (*ibid.*)\n+- **cor_p_val_raw** - p-value for Fisher-transformed correlation (Fisher, 1921; Snedecor, 1980; see also https://en.wikipedia.org/wiki/Fisher_transformation), with no family-wise error-rate correction.\n+- **cor_p_value** - p-value for Fisher-transformed correlation, adjusted for family-wise error rate (Yekutieli *et al.*, 2001). Caveat: any previous selection for features that vary notably by factor level may result in too little adjustment.\n+- **cor_ci_lower** - lower limit of 95% confidence interval for correlation (see e.g. https://en.wikipedia.org/wiki/Fisher_transformation)\n+- **cor_ci_upper** - upper limit of 95% confidence interval for correlation (*ibid.*)\n+- **mz** - *m/z* ratio for feature, copied from input variableMetadata\n+- **rt** - retention time for feature, copied from input variableMetadata\n - **level1Level2Sig** - (Only present when a test other than "none" is chosen) \'1\' when feature varies significantly across all classes (i.e., not pair-wise); \'0\' otherwise\n \n [OUT] Feature "Salience" data TABULAR\n@@ -819,6 +830,19 @@\n <citations>\n \n <citation type="doi">10.5281/zenodo.1034784</citation>\n+ \n+ <citation type="bibtex"><![CDATA[\n+ @article{Fisher_1921,\n+ author = {Fisher, R. A.},\n+ title = {{On the probable error of a coefficient of correlation deduced from a small sample}},\n+ journal = {Metron},\n+ year = {1921},\n+ volume = {1},\n+ pages = {3--32},\n+ note = {Defines the Fisher z-transformation of a coefficient of correlation. Citation adapted from http://www.citeulike.org/group/894/article/2344770},\n+ url = {https://digital.library.adelaide.edu.au/dspace/bitstream/2440/15169/1/14.pdf},\n+ }\n+ ]]></citation>\n \n <citation type="doi">10.1002/cem.2627</citation>\n \n@@ -833,6 +857,22 @@\n <citation type="doi">10.3389/fmolb.2016.00026</citation>\n \n <citation type="doi">10.1038/srep22274</citation>\n+ \n+ <citation type="bibtex"><![CDATA[\n+ @book{Snedecor_1980,\n+ author = {Snedecor, George W. and Cochran, William G.},\n+ title = {Statistical methods},\n+ publisher = {Iowa State University Press},\n+ year = {1980},\n+ pages = {186},\n+ isbn = {0813815606},\n+ language = {eng},\n+ keyword = {Statistics, Statistics as Topic -- methods},\n+ lccn = {80014582},\n+ edition = {7th ed..},\n+ address = {Ames, Iowa},\n+ }\n+ ]]></citation>\n \n <citation type="doi">10.1021/acs.jproteome.5b00354</citation>\n \n@@ -849,6 +889,8 @@\n ]]></citation>\n \n <citation type="doi">10.1021/ac0713510</citation>\n+ \n+ <citation type="doi">10.1214/aos/1013699998</citation>\n </citations>\n <!--\n vim:et:sw=4:ts=4\n'

diff -r ddcc33ff3205 -r ddaf84e15d06 w4mcorcov_calc.R
--- a/w4mcorcov_calc.R Wed Sep 05 22:31:21 2018 -0400
+++ b/w4mcorcov_calc.R Thu Nov 08 23:06:09 2018 -0500

[

b'@@ -38,10 +38,7 @@\n # strip out variables having negligible variance\n x_dataMatrix <- x_dataMatrix[,names(my_oplsda@vipVn), drop = FALSE]\n my_oplsda_suppLs_y_levels <- levels(as.factor(my_oplsda@suppLs$y))\n- # x_progress(strF(x_dataMatrix))\n- # x_progress(strF(my_oplsda))\n- #x_progress(head(my_oplsda_suppLs_y_levels))\n- #x_progress(unique(my_oplsda_suppLs_y_levels))\n+\n fctr_lvl_1 <- my_oplsda_suppLs_y_levels[1]\n fctr_lvl_2 <- my_oplsda_suppLs_y_levels[2]\n do_s_plot <- function(\n@@ -51,12 +48,8 @@\n , cor_vs_cov_x = NULL\n )\n {\n- #print(ls(x_env)) # "cplot_y" etc\n- #print(str(x_env$cplot_y)) # chr "covariance"\n if (cplot_x) {\n- #print(x_env$cplot_y) # "covariance"\n cplot_y_correlation <- (x_env$cplot_y == "correlation")\n- #print(cplot_y_correlation) # FALSE\n }\n if (is.null(cor_vs_cov_x)) {\n my_cor_vs_cov <- cor_vs_cov(\n@@ -68,7 +61,6 @@\n } else {\n my_cor_vs_cov <- cor_vs_cov_x\n }\n- # print("str(my_cor_vs_cov)")\n # str(my_cor_vs_cov)\n if (is.null(my_cor_vs_cov) || sum(!is.na(my_cor_vs_cov$tsv1$covariance)) < 2) {\n if (is.null(cor_vs_cov_x)) {\n@@ -166,6 +158,7 @@\n }\n main_cex <- min(1.0, 46.0/nchar(main_label))\n my_feature_label_slant <- -30 # slant feature labels 30 degrees downward\n+ my_pch <- sapply(X = cor_p_value, function(x) if (x < 0.01) 16 else if (x < 0.05) 17 else 18)\n plot(\n y = my_y\n , x = my_x\n@@ -177,7 +170,7 @@\n , main = main_label\n , cex.main = main_cex\n , cex = cex\n- , pch = 16\n+ , pch = my_pch\n , col = my_col\n )\n low_x <- -0.7 * lim_x\n@@ -217,12 +210,6 @@\n )\n }\n label_features <- function(x_arg, y_arg, labels_arg, slant_arg) {\n- # print("str(x_arg)")\n- # print(str(x_arg))\n- # print("str(y_arg)")\n- # print(str(y_arg))\n- # print("str(labels_arg)")\n- # print(str(labels_arg))\n if (length(labels_arg) > 0) {\n unique_slant <- unique(slant_arg)\n if (length(unique_slant) == 1) {\n@@ -851,13 +838,13 @@\n }\n \n cor_vs_cov_try <- function(\n- matrix_x\n-, ropls_x\n-, predictor_projection_x = TRUE\n-, x_progress = print\n+ matrix_x # rows are samples; columns, features\n+, ropls_x # an instance of ropls::opls\n+, predictor_projection_x = TRUE # TRUE for predictor projection; FALSE for orthogonal projection\n+, x_progress = print # function to produce progress and error messages\n ) {\n x_class <- class(ropls_x)\n- if ( !( as.character(x_class) == "opls" ) ) { # || !( attr(class(x_class),"package") == "ropls" ) )\n+ if ( !( as.character(x_class) == "opls" ) ) {\n stop(\n paste(\n "cor_vs_cov: Expected ropls_x to be of class ropls::opls but instead it was of class "\n@@ -865,57 +852,120 @@\n )\n )\n }\n+ if ( !ropls_x@suppLs$algoC == "nipals" ) {\n+ # suppLs$algoC - Character: algorithm used - "svd" for singular value decomposition; "nipals" for NIPALS\n+ stop(\n+ paste(\n+ "cor_vs_cov: Expected ropls::opls instance to have been computed by the NIPALS algorithm rather than "\n+ , ropls_x@suppLs$algoC\n+ )\n+ )\n+ }\n result <- list()\n result$projection <- projection <- if (predictor_projection_x) 1 else 2\n- # suppLs$algoC - Character: algorithm used - "svd" for singular value decomposition; "nipals" for NIPALS\n- if ( ropls_x@suppLs$algoC == "nipals") {\n- # Equations (1) and (2) from *Supplement to* Wiklund 2008, doi:10.1021/ac0713510\n- mag <- function(one_dimensional) sqrt(sum(one_dimensional * one_dimensional))\n- mag_xi <- sapply(X = 1:ncol(matrix_x), FUN = function(x) mag(matrix_x[,x]))\n- if (predictor_projection_x)\n- score_m'..b'ureID]\n # end fixes for https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/issues/1\n \n+ # build a data frame to hold the content for the tab-separated values file\n tsv1 <- data.frame(\n- featureID = featureID\n- , factorLevel1 = result$level1\n- , factorLevel2 = result$level2\n- , greaterLevel = greaterLevel\n- , projection = result$projection\n- , correlation = result$correlation\n- , covariance = result$covariance\n- , vip4p = result$vip4p\n- , vip4o = result$vip4o\n- , loadp = result$loadp\n- , loado = result$loado\n- , row.names = NULL\n+ featureID = featureID\n+ , factorLevel1 = result$level1\n+ , factorLevel2 = result$level2\n+ , greaterLevel = greaterLevel\n+ , projection = result$projection\n+ , correlation = result$correlation\n+ , covariance = result$covariance\n+ , vip4p = result$vip4p\n+ , vip4o = result$vip4o\n+ , loadp = result$loadp\n+ , loado = result$loado\n+ , cor_p_val_raw = result$p_value_raw\n+ , cor_p_value = p.adjust(p = result$p_value_raw, method = "BY")\n+ , cor_ci_lower = result$ci_lower \n+ , cor_ci_upper = result$ci_upper\n )\n- tsv1 <- tsv1[!is.na(tsv1$correlation),]\n- tsv1 <- tsv1[!is.na(tsv1$covariance),]\n- superresult$tsv1 <- tsv1\n- rownames(superresult$tsv1) <- tsv1$featureID\n+ rownames(tsv1) <- tsv1$featureID\n+\n+ # build the superresult, i.e., the result returned by this function\n+ superresult <- list()\n superresult$projection <- result$projection\n superresult$covariance <- result$covariance\n superresult$correlation <- result$correlation\n@@ -980,12 +1031,50 @@\n superresult$vip4o <- result$vip4o\n superresult$loadp <- result$loadp\n superresult$loado <- result$loado\n+ superresult$cor_p_value <- tsv1$cor_p_value\n superresult$details <- result\n- result$superresult <- superresult\n- # Include thise in case future consumers of this routine want to use it in currently unanticipated ways\n- result$oplsda <- ropls_x\n- result$predictor <- ropls_x@suppLs$y # in case future consumers of this routine want to use it in currently unanticipated ways\n+\n+ # remove any rows having NA for covariance or correlation\n+ tsv1 <- tsv1[!is.na(tsv1$correlation),]\n+ tsv1 <- tsv1[!is.na(tsv1$covariance),]\n+ superresult$tsv1 <- tsv1\n+\n+ # # I did not include these but left them commentd out in case future \n+ # # consumers of this routine want to use it in currently unanticipated ways\n+ # result$superresult <- superresult\n+ # result$oplsda <- ropls_x\n+ # result$predictor <- ropls_x@suppLs$y\n+\n return (superresult)\n }\n \n+# Code for correl.ci was adapted from correl function from:\n+# @book{\n+# Tsagris_2018,\n+# author = {Tsagris, Michail},\n+# year = {2018},\n+# link = {https://www.researchgate.net/publication/324363311_Multivariate_data_analysis_in_R},\n+# title = {Multivariate data analysis in R}\n+# }\n+# which follows\n+# https://en.wikipedia.org/wiki/Fisher_transformation#Definition\n+\n+correl.ci <- function(r, n, a = 0.05, rho = 0) {\n+ ## r is the calculated correlation coefficient for n pairs\n+ ## a is the significance level\n+ ## rho is the hypothesised correlation\n+ zh0 <- atanh(rho) # 0.5*log((1+rho)/(1-rho)), i.e., Fisher\'s z-transformation for Ho\n+ zh1 <- atanh(r) # 0.5*log((1+r)/(1-r)), i.e., Fisher\'s z-transformation for H1\n+ se <- (1 - r^2)/sqrt(n - 3) ## standard error for Fisher\'s z-transformation of Ho\n+ test <- (zh1 - zh0)/se ### test statistic\n+ pvalue <- 2*(1 - pnorm(abs(test))) ## p-value\n+ zL <- zh1 - qnorm(1 - a/2)*se\n+ zH <- zh1 + qnorm(1 - a/2)*se\n+ fishL <- tanh(zL) # (exp(2*zL)-1)/(exp(2*zL)+1), i.e., lower confidence limit\n+ fishH <- tanh(zH) # (exp(2*zH)-1)/(exp(2*zH)+1), i.e., upper confidence limit\n+ CI <- c(fishL, fishH)\n+ names(CI) <- c(\'lower\', \'upper\')\n+ list(correlation = r, p.value = pvalue, CI = CI)\n+}\n+\n # vim: sw=2 ts=2 et :\n'