Mercurial > repos > miller-lab > genome_diversity
annotate add_fst_column.xml @ 28:184d14e4270d
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author | Richard Burhans <burhans@bx.psu.edu> |
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date | Wed, 17 Jul 2013 12:46:46 -0400 |
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1 <tool id="gd_add_fst_column" name="Per-SNP FSTs" version="1.2.0"> |
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2 <description>: Compute a fixation index score for each SNP</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 add_fst_column.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_reads' '$input_type.data_source.min_qual' |
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19 #else if $input_type.data_source.choice == '1' |
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20 '0' '0' |
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21 #end if |
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22 #else if $input_type.choice == '1' |
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23 'gd_genotype' '1' '0' '0' |
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24 #end if |
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25 '$retain' '$discard_fixed' '$biased' '$output' '$ind_arg' |
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26 </command> |
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27 |
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28 <inputs> |
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29 <conditional name="input_type"> |
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30 <param name="choice" type="select" format="integer" label="Input format"> |
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31 <option value="0" selected="true">gd_snp</option> |
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32 <option value="1">gd_genotype</option> |
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33 </param> |
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34 |
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35 <when value="0"> |
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36 <param name="input" type="data" format="gd_snp" label="SNP dataset" /> |
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37 |
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38 <conditional name="data_source"> |
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39 <param name="choice" type="select" format="integer" label="Frequency metric"> |
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40 <option value="0">sequence coverage</option> |
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41 <option value="1" selected="true">estimated genotype</option> |
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42 </param> |
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43 <when value="0"> |
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44 <param name="min_reads" type="integer" min="0" value="0" label="Minimum total read count for a population" /> |
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45 <param name="min_qual" type="integer" min="0" value="0" label="Minimum individual genotype quality" /> |
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46 </when> |
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47 <when value="1"/> |
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48 </conditional> |
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49 </when> |
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50 <when value="1"> |
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51 <param name="input" type="data" format="gd_genotype" label="Genotype dataset" /> |
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52 </when> |
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53 </conditional> |
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54 |
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55 <param name="p1_input" type="data" format="gd_indivs" label="Population 1 individuals" /> |
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56 <param name="p2_input" type="data" format="gd_indivs" label="Population 2 individuals" /> |
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57 |
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58 <param name="retain" type="select" label="If a SNP is below minimum"> |
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59 <option value="0" selected="true">skip SNP</option> |
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60 <option value="1">set FST = -1</option> |
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61 </param> |
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62 |
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63 <param name="discard_fixed" type="select" label="For SNPs that appear to be fixed across both populations"> |
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64 <option value="0">retain</option> |
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65 <option value="1" selected="true">delete</option> |
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66 </param> |
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67 |
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68 <param name="biased" type="select" label="FST estimator"> |
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69 <option value="0">Wright's original definition</option> |
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70 <option value="1">the Weir-Cockerham estimator</option> |
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71 <option value="2" selected="true">the Reich-Patterson estimator</option> |
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72 </param> |
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73 |
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74 </inputs> |
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75 |
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76 <outputs> |
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77 <data name="output" format="input" format_source="input" metadata_source="input" /> |
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78 </outputs> |
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79 |
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80 <tests> |
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81 <test> |
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82 <param name="input" value="test_in/sample.gd_snp" ftype="gd_snp" /> |
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83 <param name="p1_input" value="test_in/a.gd_indivs" ftype="gd_indivs" /> |
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84 <param name="p2_input" value="test_in/b.gd_indivs" ftype="gd_indivs" /> |
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85 <param name="data_source" value="0" /> |
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86 <param name="min_reads" value="3" /> |
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87 <param name="min_qual" value="0" /> |
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88 <param name="retain" value="0" /> |
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89 <param name="discard_fixed" value="1" /> |
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90 <param name="biased" value="0" /> |
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91 <output name="output" file="test_out/add_fst_column/add_fst_column.gd_snp" /> |
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92 </test> |
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93 </tests> |
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94 |
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95 <help> |
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96 |
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97 **Dataset formats** |
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98 |
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99 The input datasets are in gd_snp_, gd_genotype_, and gd_indivs_ formats. |
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100 The output dataset is in gd_snp_ or gd_genotype_ format. (`Dataset missing?`_) |
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101 |
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102 .. _gd_snp: ./static/formatHelp.html#gd_snp |
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103 .. _gd_genotype: ./static/formatHelp.html#gd_genotype |
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104 .. _gd_indivs: ./static/formatHelp.html#gd_indivs |
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105 .. _Dataset missing?: ./static/formatHelp.html |
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106 |
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107 ----- |
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108 |
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109 **What it does** |
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110 |
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111 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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112 |
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113 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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114 |
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115 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. |
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116 |
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117 The user specifies whether the SNPs that violate the lower bound should be ignored or the Fst set to -1. |
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118 |
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119 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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120 |
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121 Finally, the user chooses which definition of Fst to use: Wright's original definition, the Weir-Cockerham unbiased estimator, or the Reich-Patterson estimator. |
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122 |
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123 A column is appended to the SNP table giving the Fst for each retained SNP. |
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124 |
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125 References: |
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126 |
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127 Sewall Wright (1951) The genetical structure of populations. Ann Eugen 15:323-354. |
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128 |
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129 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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130 |
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131 Weir, B.S. 1996. Population substructure. Genetic data analysis II, pp. 161-173. Sinauer Associates, Sundand, MA. |
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132 |
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133 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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134 |
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135 Their effectiveness for computing FSTs when there are many SNPs but few individuals is discussed in the following paper. |
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136 |
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137 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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138 |
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139 ----- |
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140 |
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141 **Example** |
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142 |
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143 - input, SNP table:: |
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144 |
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145 #{"column_names":["scaf","pos","A","B","qual","ref","rpos","rnuc","1A","1B","1G","1Q","2A","2B","2G","2Q","3A","3B","3G","3Q","4A","4B","4G","4Q", |
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146 #"5A","5B","5G","5Q","6A","6B","6G","6Q","pair","dist","prim","rflp"],"dbkey":"canFam2", |
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147 #"individuals":[["PB1",9],["PB2",13],["PB3",17],["PB4",21],["PB6",25],["PB8",29]], |
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148 #"pos":2,"rPos":7,"ref":6,"scaffold":1,"species":"bear"} |
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149 Contig161_chr1_4641264_4641879 115 C T 73.5 chr1 4641382 C 6 0 2 45 8 0 2 51 15 0 2 72 5 0 2 42 6 0 2 45 10 0 2 57 Y 54 0.323 0 |
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150 Contig113_chr5_11052263_11052603 28 C T 38.2 chr5 11052280 C 1 2 1 12 3 2 1 10 5 0 2 42 2 1 2 13 3 0 2 36 8 0 2 51 Y 161 +99. 0 |
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151 Contig215_chr5_70946445_70947428 363 T G 28.2 chr5 70946809 C 4 0 2 39 0 5 0 12 9 0 2 54 6 0 2 45 3 3 2 1 9 0 2 54 N 43 0.153 0 |
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152 etc. |
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153 |
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154 - input, Population 1 individuals:: |
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155 |
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156 9 PB1 |
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157 13 PB2 |
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158 |
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159 - input, Population 2 individuals:: |
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160 |
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161 17 PB3 |
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162 21 PB4 |
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163 |
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164 - output (minimum read count of 3, discard fixed):: |
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166 Contig113_chr5_11052263_11052603 28 C T 38.2 chr5 11052280 C 1 2 1 12 3 2 1 10 5 0 2 42 2 1 2 13 3 0 2 36 8 0 2 51 Y 161 +99. 0 0.1636 |
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167 Contig215_chr5_70946445_70947428 363 T G 28.2 chr5 70946809 C 4 0 2 39 0 5 0 12 9 0 2 54 6 0 2 45 3 3 2 1 9 0 2 54 N 43 0.153 0 0.3846 |
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168 etc. |
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169 |
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170 </help> |
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171 </tool> |