Mercurial > repos > ethevenot > univariate

annotate univariate_config.xml @ 4:3017385625f6 draft

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planemo upload for repository https://github.com/workflow4metabolomics/univariate.git commit a81d4cc1df719dcc66def660927abda74972afaa
author ethevenot
date Thu, 11 Jan 2018 10:21:17 -0500
parents 140290de7986
children 5687435b182c
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3017385625f6 planemo upload for repository https://github.com/workflow4metabolomics/univariate.git commit a81d4cc1df719dcc66def660927abda74972afaa
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1 <tool id="Univariate" name="Univariate" version="2.2.4">
0
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2 <description>Univariate statistics</description>
2
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3
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4 <requirements>
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5 <requirement type="package">r-batch</requirement>
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6 <requirement type="package">r-PMCMR</requirement>
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7 </requirements>
0
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8
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9 <stdio>
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10 <exit_code range="1:" level="fatal" />
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11 </stdio>
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12
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13 <command><![CDATA[
2
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14 Rscript $__tool_directory__/univariate_wrapper.R
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15
2
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16 dataMatrix_in "$dataMatrix_in"
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17 sampleMetadata_in "$sampleMetadata_in"
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18 variableMetadata_in "$variableMetadata_in"
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19
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20 facC "$facC"
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21 tesC "$tesC"
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22 adjC "$adjC"
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23 thrN "$thrN"
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25 variableMetadata_out "$variableMetadata_out"
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26 figure "$figure"
2
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27 information "$information"
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28 ]]></command>
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29 <inputs>
2
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30 <param name="dataMatrix_in" label="Data matrix file" type="data" format="tabular" help="variable x sample, decimal: '.', missing: NA, mode: numerical, sep: tabular" />
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31 <param name="sampleMetadata_in" label="Sample metadata file" type="data" format="tabular" help="sample x metadata, decimal: '.', missing: NA, mode: character and numerical, sep: tabular" />
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32 <param name="variableMetadata_in" label="Variable metadata file" type="data" format="tabular" help="variable x metadata, decimal: '.', missing: NA, mode: character and numerical, sep: tabular" />
0
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33 <param name="facC" label="Factor of interest" type="text" help="Name of the column of the sample metadata table corresponding to the qualitative or quantitative variable"/>
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34 <param name="tesC" label="Test" type="select" help="">
2
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35 <option value="ttest">ttest (qualitative, 2 levels)</option>
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36 <option value="wilcoxon">Wilcoxon test (qualitative, 2 levels)</option>
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37 <option value="anova">Analysis of variance (qualitative, more than 2 levels)</option>
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38 <option value="kruskal">Kruskal-Wallis rank test (qualitative, more than 2 levels)</option>
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39 <option value="pearson">Pearson correlation test (quantitative)</option>
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40 <option value="spearman">Spearman correlation rank test (quantitative)</option>
0
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41 </param>
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42 <param name="adjC" label="Method for multiple testing correction" type="select" help="">
2
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43 <option value="fdr">fdr</option>
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44 <option value="BH">BH</option>
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45 <option value="bonferroni">bonferroni</option>
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46 <option value="BY">BY</option>
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47 <option value="hochberg">hochberg</option>
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48 <option value="holm">holm</option>
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49 <option value="hommel">hommel</option>
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50 <option value="none">none</option>
0
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51 </param>
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52 <param name="thrN" type="float" value="0.05" label="(Corrected) p-value significance threshold" help="Must be between 0 and 1"/>
2
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53 </inputs>
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54
0
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55 <outputs>
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56 <data name="variableMetadata_out" label="${tool.name}_${variableMetadata_in.name}" format="tabular" ></data>
3
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57 <data name="figure" label="${tool.name}_figure.pdf" format="pdf"/>
2
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58 <data name="information" label="${tool.name}_information.txt" format="txt"/>
0
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59 </outputs>
2
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60
0
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61 <tests>
2
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62 <test>
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63 <param name="dataMatrix_in" value="dataMatrix.tsv"/>
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64 <param name="sampleMetadata_in" value="sampleMetadata.tsv"/>
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65 <param name="variableMetadata_in" value="variableMetadata.tsv"/>
3
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66 <param name="facC" value="qual"/>
2
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67 <param name="tesC" value="kruskal"/>
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68 <param name="adjC" value="fdr"/>
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69 <param name="thrN" value="0.05"/>
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70 <output name="variableMetadata_out" file="output-variableMetadata.tsv"/>
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71 </test>
0
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72 </tests>
2
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73
0
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74 <help>
3
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75
0
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76 .. class:: infomark
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78 | **Tool update: See the 'NEWS' section at the bottom of the page**
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80 ---------------------------------------------------
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81
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82 .. class:: infomark
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83
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84 **Authors**
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85
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86 | **Marie Tremblay-Franco (marie.tremblay-franco@toulouse.inra.fr)** and **Etienne Thevenot (etienne.thevenot@cea.fr)** wrote this wrapper of R univariate statistical tests.
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87 | MetaboHUB: The French National Infrastructure for Metabolomics and Fluxomics (http://www.metabohub.fr/en)
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88
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89 ---------------------------------------------------
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90
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91 .. class:: infomark
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92
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93 **Please cite**
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94
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95 R Core Team (2013). R: A language and Environment for Statistical Computing. http://www.r-project.org
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96
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97 ---------------------------------------------------
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98
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99 .. class:: infomark
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100
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101 **References**
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102
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103 | Benjamini Y. and Hochberg Y. (1995). Controlling the false discovery rate: a practical and powerful approach for multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57:289-300.
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104 | Dalgaard P. (2002). Introductory statistics with R. Springer.
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105 | Kvam P. and Vidakovic B. (2007). Nonparametric statistics with applications to science and engineering. Wiley.
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106 | Van Belle G., Fisher L., Heagerty P. and Lumley T. (2004). Biostatistics - a methodology for the health sciences. Wiley.
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107 | Pohlert T. (2015). PMCMR: Calculate pairwise multiple comparisons of mean rank sums. R package on CRAN.
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108
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109 ---------------------------------------------------
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110
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111 =====================
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112 Univariate statistics
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113 =====================
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114
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115 -----------
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116 Description
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117 -----------
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118
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119 | The module performs two sample tests (t-test and Wilcoxon rank test), analysis of variance and Kruskal-Wallis rank test, and correlation tests (by using either the pearson or the spearman correlation)
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120
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121 -----------------
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122 Workflow position
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123 -----------------
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124
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125 .. image:: univariate_workflowPositionImage.png
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126 :width: 584
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127
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128 -----------
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129 Input files
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130 -----------
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131
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132 +------------------------------+------------+
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133 | File | Format |
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134 +==============================+============+
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135 | 1) Data matrix | tabular |
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136 +------------------------------+------------+
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137 | 2) Sample metadata | tabular |
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138 +------------------------------+------------+
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139 | 3) Variable metadata | tabular |
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140 +------------------------------+------------+
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141
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142 ----------
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143 Parameters
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144 ----------
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145
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146 Data matrix file
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147 | variable x sample **dataMatrix** tabular separated file of the numeric data matrix, with . as decimal, and NA for missing values; the table must not contain metadata apart from row and column names; the row and column names must be identical to the rownames of the sample and variable metadata, respectively (see below)
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148 |
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149
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150 Sample metadata file
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151 | sample x metadata **sampleMetadata** tabular separated file of the numeric and/or character sample metadata, with . as decimal and NA for missing values
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152 |
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153
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154 Variable metadata file
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155 | variable x metadata **variableMetadata** tabular separated file of the numeric and/or character variable metadata, with . as decimal and NA for missing values
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156 |
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157
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158 Factor
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159 | Column of the sample metadata table to be used as qualitative factor (t-test, Wilcoxon test, Analysis of variance, Kruskal-Wallis test) or quantitative variable (correlation)
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160 |
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161
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162 Test
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163 | Depending on the factor of interest (qualitative with 2 or more levels, or quantitative), and on the normality of the sample values (determining whether a parametric or nonparametric test is required), you can choose one of the 6 tests available:
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164
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165
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166 +---------------------------+------------------+----------------------+----------------------+
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167 | Factor to be tested | Number of levels | Parametric test | Nonparametric test |
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168 +===========================+==================+======================+======================+
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169 | Qualitative | 2 | t-test | Wilcoxon test |
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170 + +------------------+----------------------+----------------------+
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171 | | > 2 | Analysis of variance | Kruskal-Wallis |
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172 +---------------------------+------------------+----------------------+----------------------+
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173 | Quantitative | | Pearson correlation | Spearman correlation |
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174 +---------------------------+------------------+----------------------+----------------------+
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175
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176 Method for multiple testing correction
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177 | The 7 methods implemented in the 'p.adjust' R function are available and documented as follows:
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178 | "The adjustment methods include the Bonferroni correction ("bonferroni") in which the p-values are multiplied by the number of comparisons. Less conservative corrections are also included by Holm (1979) ("holm"), Hochberg (1988) ("hochberg"), Hommel (1988) ("hommel"), Benjamini and Hochberg (1995) ("BH" or its alias "fdr"), and Benjamini and Yekutieli (2001) ("BY"), respectively. A pass-through option ("none") is also included. The set of methods are contained in the p.adjust.methods vector for the benefit of methods that need to have the method as an option and pass it on to p.adjust. The first four methods are designed to give strong control of the family-wise error rate. There seems no reason to use the unmodified Bonferroni correction because it is dominated by Holm's method, which is also valid under arbitrary assumptions. Hochberg's and Hommel's methods are valid when the hypothesis tests are independent or when they are non-negatively associated (Sarkar, 1998; Sarkar and Chang, 1997). Hommel's method is more powerful than Hochberg's, but the difference is usually small and the Hochberg p-values are faster to compute. The "BH" (aka "fdr") and "BY" method of Benjamini, Hochberg, and Yekutieli control the false discovery rate, the expected proportion of false discoveries amongst the rejected hypotheses. The false discovery rate is a less stringent condition than the family-wise error rate, so these methods are more powerful than the others."
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179 |
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180
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181 (Corrected) p-value significance threshold
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182 |
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183 |
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184
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185
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186 ------------
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187 Output files
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188 ------------
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189
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190 variableMetadata_out.tabular
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191 | **variableMetadata** file identical to the file given as argument, except that (at least) three columns have been added:
3
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192 | 1) [factor]_[test]_[class'a'].[class'b']_dif or [factor]_[test]_cor: difference of the means (ttest) or the medians (wilcoxon) between the two classes, or 'pearson' or 'spearman' correlations
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193 | 2) [factor]_[test]_[class'a'].[class'b']_[method] or [factor]_[test]_[method]: adjusted p-values
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194 | 3) [factor]_[test]_[class'a'].[class'b']_sig or [factor]_[test]_sig: significance (coded as '1' if below the threshold and '0' otherwise)
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195 | In the case of 'anova' and 'kruskal', the columns 2) and 3) appear first to give the results from the ANOVA or Kruskal Wallis test, and then the results of the pairwise comparisons are reported in additional columns (otherwise NA in these columns): in the case of ANOVA, the Tukey HSD post-hoc analysis is used (for each comparison, the difference between means, p value, and significance are provided); in the case of Kruskal Wallis, the Nemenyi is performed (PMCMR package) (for each pairwise comparison, the difference between medians, p value and significance are provided); note that since version 2.2.0, the p-values of the post-hoc pairwise comparisons (ANOVA or Kruskal) are further corrected for multiple testing over all variables (as the p-value of the omnibus test in column 2)
0
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196 |
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197
3
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198 figure.pdf
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199 | File containing the graphics of all significant tests: boxplots (respectively scatterplots with the regression line in red and the R2 value) are displayed when the factor of interest is qualitative (respectively quantitative). The variable name and the corrected p-value is indicated in the title of each plot
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200 |
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201
0
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202 information.txt
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203 | File with all messages and warnings generated during the computation
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204 |
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205
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206 ---------------------------------------------------
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207
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208 ---------------
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209 Working example
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210 ---------------
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211
2
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212 .. class:: infomark
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213
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214 See the **W4M00001a_sacurine-subset-statistics**, **W4M00001b_sacurine-subset-complete**, **W4M00002_mtbls2**, **W4M00003_diaplasma** shared histories in the **Shared Data/Published Histories** menu (https://galaxy.workflow4metabolomics.org/history/list_published)
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215
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216 ---------------------------------------------------
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217
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218 ----
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219 NEWS
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220 ----
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221
4
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222 CHANGES IN VERSION 2.2.4
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223 ========================
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224
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225 MINOR MODIFICATION
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226
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227 Internal minor modifications for building and testing
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228
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229
3
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230 CHANGES IN VERSION 2.2.0
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231 ========================
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232
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233 MAJOR MODIFICATION
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234
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235 ANOVA and Kruskal-Wallis: The p-values of the post-hoc tests (i.e. from pairwise comparisons) are now further corrected for multiple testing over all variables (previously, only the p-value of the omnibus test was corrected over all variables)
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236
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237 MINOR MODIFICATION
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238
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239 All values in the 'dif', adjusted p-value, and 'sig' columns are now displayed (previously, the values were set to NA when the p-value of the omnibus test was not significant)
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240
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241 NEW FEATURE
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242
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243 Graphic: a single pdf file containing the graphics of all significant tests is now produced as '_figure.pdf' output: boxplots (respectively scatterplots with the regression line in red and the R2 value) are displayed when the factor of interest is qualitative (respectively quantitative). The corrected p-value is indicated in the title of each plot
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244
2
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245 CHANGES IN VERSION 2.1.4
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246 ========================
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247
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248 NEW FEATURE
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249
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250 Level names are now separated by '.' instead of '-' previously in the column names of the output variableMetadata table (e.g., 'jour_ttest_J3.J10_fdr' instead of 'jour_ttest_J3-J10_fdr' previously)
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251
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252 INTERNAL MODIFICATIONS
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253
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254 Minor internal changes for toolshed export
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255
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256 CHANGES IN VERSION 2.1.2
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257 ========================
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258
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259 INTERNAL MODIFICATIONS
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260
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261 Minor internal changes for toolshed export
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262
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263 CHANGES IN VERSION 2.1.1
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264 ========================
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265
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266 INTERNAL MODIFICATIONS
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267
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268 Internal handling of 'NA' p-values (e.g. when intensities are identical in all samples)
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269
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270 CHANGES IN VERSION 2.0.1
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271 ========================
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272
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273 NEW FEATURE
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274
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275 (corrected) p-value threshold can be set to any value between 0 and 1
3
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276
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277 </help>
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278
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279 <citations>
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280 <citation type="bibtex">@Manual{,
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281 title = {R: A Language and Environment for Statistical Computing},
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282 author = {{R Core Team}},
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283 organization = {R Foundation for Statistical Computing},
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284 address = {Vienna, Austria},
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285 year = {2016},
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286 url = {https://www.R-project.org/},
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287 }</citation>
4
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288 <citation type="doi">10.1021/acs.jproteome.5b00354</citation>
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289 <citation type="doi">10.1016/j.biocel.2017.07.002</citation>
3
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290 <citation type="doi">10.1093/bioinformatics/btu813</citation>
140290de7986 planemo upload for repository https://github.com/workflow4metabolomics/univariate.git commit 27bc6157f43574f038b3fb1be1f46ce4786e24b1
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291 </citations>
140290de7986 planemo upload for repository https://github.com/workflow4metabolomics/univariate.git commit 27bc6157f43574f038b3fb1be1f46ce4786e24b1
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292
0
ef64d3752050 planemo upload for repository https://github.com/workflow4metabolomics/univariate.git commit ca0e312e1c986c45310f37effe031f60009fbcab
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293 </tool>