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annotate average_fst.xml @ 36:51cd0307fb70

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Phylip's extra ouputs are now stored in the job working directory
author Richard Burhans <burhans@bx.psu.edu>
date Wed, 20 Nov 2013 16:32:01 -0500
parents a631c2f6d913
children
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1 <tool id="gd_average_fst" name="Overall FST" version="1.3.0">
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2 <description>: Estimate the relative fixation index between two populations</description>
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3
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4 <command interpreter="python">
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5 #import json
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6 #import base64
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7 #import zlib
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8 #set $ind_names = $input.dataset.metadata.individual_names
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9 #set $ind_colms = $input.dataset.metadata.individual_columns
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10 #set $ind_dict = dict(zip($ind_names, $ind_colms))
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11 #set $ind_json = json.dumps($ind_dict, separators=(',',':'))
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12 #set $ind_comp = zlib.compress($ind_json, 9)
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13 #set $ind_arg = base64.b64encode($ind_comp)
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14 average_fst.py '$input' '$p1_input' '$p2_input'
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15 #if $input_type.choice == '0'
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16 'gd_snp' '$input_type.data_source.choice'
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17 #if $input_type.data_source.choice == '0'
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18 '$input_type.data_source.min_value'
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19 #else if $input_type.data_source.choice == '1'
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20 '1'
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21 #end if
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22 #else if $input_type.choice == '1'
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23 'gd_genotype' '1' '1'
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24 #end if
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25 '$discard_fixed' '$output'
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26 #if $use_randomization.choice == '0'
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27 '0' '/dev/null'
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28 #else if $use_randomization.choice == '1'
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29 '$use_randomization.shuffles' '$use_randomization.p0_input'
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30 #end if
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31 '$ind_arg'
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32 </command>
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33
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34 <inputs>
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35 <conditional name="input_type">
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36 <param name="choice" type="select" format="integer" label="Input format">
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37 <option value="0" selected="true">gd_snp</option>
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38 <option value="1">gd_genotype</option>
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39 </param>
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40
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41 <when value="0">
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42 <param name="input" type="data" format="gd_snp" label="SNP dataset" />
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43
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44 <conditional name="data_source">
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45 <param name="choice" type="select" format="integer" label="Frequency metric">
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46 <option value="0">sequence coverage</option>
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47 <option value="1" selected="true">estimated genotype</option>
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48 </param>
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49
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50 <when value="0">
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51 <param name="min_value" type="integer" min="1" value="1" label="Minimum total read count for a population" />
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52 </when>
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53
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54 <when value="1"/>
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55 </conditional>
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56 </when>
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57
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58 <when value="1">
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59 <param name="input" type="data" format="gd_genotype" label="Genotype dataset" />
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60 </when>
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61 </conditional>
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62
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63 <param name="p1_input" type="data" format="gd_indivs" label="Population 1 individuals" />
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64 <param name="p2_input" type="data" format="gd_indivs" label="Population 2 individuals" />
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65
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66 <param name="discard_fixed" type="select" label="For SNPs that appear to be fixed across both populations">
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67 <option value="0">retain</option>
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68 <option value="1" selected="true">delete</option>
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69 </param>
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70
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71 <conditional name="use_randomization">
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72 <param name="choice" type="select" format="integer" label="Use randomization">
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73 <option value="0" selected="true">no</option>
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74 <option value="1">yes</option>
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75 </param>
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76 <when value="0" />
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77 <when value="1">
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78 <param name="shuffles" type="integer" min="0" value="0" label="Shuffles" />
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79 <param name="p0_input" type="data" format="gd_indivs" label="Individuals for randomization" />
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80 </when>
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81 </conditional>
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82 </inputs>
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83
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84 <outputs>
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85 <data name="output" format="txt" />
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86 </outputs>
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87
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88 <requirements>
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89 <requirement type="package" version="0.1">gd_c_tools</requirement>
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90 </requirements>
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91
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92 <tests>
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93 <test>
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94 <param name="input" value="test_in/sample.gd_snp" ftype="gd_snp" />
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95 <param name="p1_input" value="test_in/a.gd_indivs" ftype="gd_indivs" />
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96 <param name="p2_input" value="test_in/b.gd_indivs" ftype="gd_indivs" />
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97 <param name="ds_choice" value="0" />
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98 <param name="min_value" value="3" />
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99 <param name="discard_fixed" value="1" />
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100 <param name="choice" value="0" />
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101 <output name="output" file="test_out/average_fst/average_fst.txt" />
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102 </test>
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103 </tests>
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104
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105 <help>
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106
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107 **Dataset formats**
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108
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109 The input datasets are in gd_snp_, gd_genotype_, and gd_indivs_ formats.
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110 The output dataset is in text_ format. (`Dataset missing?`_)
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111
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112 .. _gd_snp: ./static/formatHelp.html#gd_snp
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113 .. _gd_genotype: ./static/formatHelp.html#gd_genotype
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114 .. _gd_indivs: ./static/formatHelp.html#gd_indivs
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115 .. _text: ./static/formatHelp.html#text
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116 .. _Dataset missing?: ./static/formatHelp.html
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117
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118 -----
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119
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120 **What it does**
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121
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122 The user specifies a SNP table and two "populations" of individuals, both previously defined using the Galaxy tool to specify individuals from a SNP table. No individual can be in both populations. Other choices are as follows.
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123
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124 Frequency metric. The allele frequencies of a SNP in the two populations can be estimated either by the total number of reads of each allele (if the table is in gd_snp format, but not with gd_genotype), or by adding the frequencies inferred from genotypes of individuals in the populations.
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125
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126 After specifying the frequency metric, the user sets lower bounds on amount of data required at a SNP. For estimating the FST using read counts, the bound is the minimum count of reads of the two alleles in a population. For estimations based on genotype, the bound is the minimum reported genotype quality per individual. SNPs not meeting these lower bounds are ignored.
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127
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128 The user specifies whether SNPs where both populations appear to be fixed for the same allele should be retained or discarded.
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129
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130 Finally, the user decides whether to use randomizations. If so, then the user specifies how many randomly generated population pairs (retaining the numbers of individuals of the originals) to generate, as well as the "population" of additional individuals (not in the first two populations) that can be used in the randomization process.
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131
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132 The program prints the following measures of FST for the two populations.
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133
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134 1. The Reich-Patterson estimator (average over FSTs for all SNPs).
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135 2. The population-based Reich-Patterson estimator.
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136 3. The formulation by Sewall Wright (average over FSTs for all SNPs).
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137 4. The Weir-Cockerham estimator (average over FSTs for all SNPs).
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138
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139 If randomizations were requested, it prints a summary for each of the four definitions of FST that includes the maximum and average value, and the highest-scoring population pair (if any scored higher than the two user-specified populations).
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140
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141 References:
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142
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143 Sewall Wright (1951) The genetical structure of populations. Ann Eugen 15:323-354.
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144
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145 Weir, B.S. and Cockerham, C. Clark (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358-1370.
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146
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147 Weir, B.S. 1996. Population substructure. Genetic data analysis II, pp. 161-173. Sinauer Associates, Sundand, MA.
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148
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149 David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, and Lalji Singh (2009) Reconstructing Indian population history. Nature 461:489-494, especially Supplement 2.
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150
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151 Their effectiveness for computing FSTs when there are many SNPs but few individuals is discussed in the following paper.
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152
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153 Eva-Maria Willing, Christine Dreyer, Cock van Oosterhout (2012) Estimates of genetic differentiation measured by FST do not necessarily require large sample sizes when using many SNP markers. PLoS One 7:e42649.
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154
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155 -----
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156
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157 **Example**
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158
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159 - output::
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160
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161 Using 37847 SNPs, we compute:
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162 Average Reich-Patterson FST is 0.31012.
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163 The population-based Reich-Patterson Fst is 0.33625.
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164 Average Wright FST is 0.22810.
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165 Average Weir-Cockerham FST is 0.30813.
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166
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167 </help>
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168 </tool>