Mercurial > repos > iuc > bigwig_outlier_bed

annotate bigwig_outlier_bed.xml @ 0:ebcd48f183b3 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/bigwig_outlier_bed commit 091caba3c5b066b293745ccee5cd31132fec3b4b
author iuc
date Fri, 05 Jul 2024 06:00:15 +0000
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ebcd48f183b3 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/bigwig_outlier_bed commit 091caba3c5b066b293745ccee5cd31132fec3b4b
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1 <tool name="Bigwig extremes to bed features" id="bigwig_outlier_bed" version="0.1.4" profile="22.05">
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2 <description>Writes high and low bigwig runs as features in a bed file</description>
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3 <edam_topics>
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4 <edam_topic>topic_0157</edam_topic>
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5 <edam_topic>topic_0092</edam_topic>
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6 </edam_topics>
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7 <edam_operations>
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8 <edam_operation>operation_0337</edam_operation>
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9 </edam_operations>
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10 <xrefs>
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11 <xref type="bio.tools">bigtools</xref>
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12 </xrefs>
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13 <requirements>
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14 <requirement type="package" version="3.12.3">python</requirement>
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15 <requirement type="package" version="2.0.0">numpy</requirement>
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16 <requirement type="package" version="0.1.4">pybigtools</requirement>
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17 </requirements>
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18 <required_files>
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19 <include path="bigwig_outlier_bed.py"/>
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20 </required_files>
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21 <version_command><![CDATA[python -c "import pybigtools; from importlib.metadata import version; print(version('pybigtools'))"]]></version_command>
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22 <command><![CDATA[python '${__tool_directory__}/bigwig_outlier_bed.py'
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23 --bigwig
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24 #for bw in $bigwig:
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25 '$bw'
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26 #end for
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27 --bigwiglabels
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28 #for bw in $bigwig:
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29 '$bw.name'
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30 #end for
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31 --outbeds '$outbeds'
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32 #if $outbeds in ['outhilo', 'outall']:
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33 --bedouthilo '$bedouthilo'
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34 #end if
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35 #if $outbeds in ['outhi', 'outall', 'outlohi']:
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36 --bedouthi '$bedouthi'
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37 #end if
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38 #if $outbeds in ['outlo', 'outall', 'outlohi']:
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39 --bedoutlo '$bedoutlo'
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40 #end if
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41 --minwin '$minwin'
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42 #if $qhi:
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43 --qhi '$qhi'
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44 #end if
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45 #if $qlo:
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46 --qlo '$qlo'
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47 #end if
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48 #if $tableout == "create":
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49 --tableoutfile '$tableoutfile'
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50 #end if
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51 ]]></command>
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52 <inputs>
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53 <param name="bigwig" type="data" optional="false" label="Choose one or more bigwig file(s) to return outlier regions as a bed file"
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54 help="If more than one, MUST all use the same reference sequence to be displayable. Feature names will include the bigwig label." format="bigwig" multiple="true"/>
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55 <param name="minwin" type="integer" value="10" label="Minimum continuous bases to count as a high or low bed feature"
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56 help="Continuous features as long or longer than this window size will appear as bed features"/>
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57 <param name="qhi" type="float" value="0.99" label="Quantile cutoff for a high region - 0.99 will cut off at or above the 99th percentile" help="Required" optional="false"/>
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58 <param name="qlo" type="float" value="0.01" label="Quantile cutoff for a low region - 0.01 will cut off at or below the 1st percentile." help="Optional" optional="true"/>
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59 <param name="outbeds" type="select" label="Select the required bed file outputs" help="Any combination of the 3 different kinds of bed file output can be made">
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60 <option value="outhilo" selected="true">Make 1 bed output with both low and high regions</option>
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61 <option value="outhi">Make 1 bed output with high regions only</option>
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62 <option value="outlo">Make 1 bed output with low regions only</option>
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63 <option value="outall">Make 3 bed outputs with low and high together in one, high in one and low in the other</option>
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64 <option value="outlohi">Make 2 bed outputs with high in one and low in the other</option>
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65 </param>
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66 <param name="tableout" type="select" label="Write a table showing contig statistics for each bigwig input" help="">
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67 <option value="donotmake">Do not create this report</option>
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68 <option value="create" selected="true">Create this report</option>
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69 </param>
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70 </inputs>
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71 <outputs>
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72 <data name="bedouthilo" format="bed" label="High_and_low_bed" hidden="false">
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73 <filter>outbeds in ["outall", "outhilo"]</filter>
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74 </data>
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75 <data name="bedouthi" format="bed" label="High bed" hidden="false">
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76 <filter>outbeds in ["outall", "outlohi", "outhi"]</filter>
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77 </data>
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78 <data name="bedoutlo" format="bed" label="Low bed" hidden="false">
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79 <filter>outbeds in ["outall", "outlohi", "outlo"]</filter>
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80 </data>
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81 <data name="tableoutfile" format="tabular" label="Contig statistics" hidden="false">
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82 <filter>tableout == "create"</filter>
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83 </data>
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84 </outputs>
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85 <tests>
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86 <test expect_num_outputs="1">
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87 <output name="bedouthilo" value="bedouthilo_sample" compare="diff" lines_diff="0"/>
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88 <param name="outbeds" value="outhilo"/>
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89 <param name="bigwig" value="bigwig_sample"/>
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90 <param name="minwin" value="10"/>
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91 <param name="qhi" value="0.99"/>
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92 <param name="qlo" value="0.01"/>
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93 <param name="tableout" value="donotmake"/>
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94 </test>
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95 <test expect_num_outputs="2">
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96 <output name="bedouthilo" value="bedouthilo_sample" compare="diff" lines_diff="0"/>
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97 <output name="tableoutfile" value="table_sample" compare="diff" lines_diff="0"/>
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98 <param name="outbeds" value="outhilo"/>
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99 <param name="bigwig" value="bigwig_sample"/>
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100 <param name="minwin" value="10"/>
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101 <param name="qhi" value="0.99"/>
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102 <param name="qlo" value="0.01"/>
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103 <param name="tableout" value="create"/>
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104 </test>
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105 <test expect_num_outputs="3">
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106 <output name="bedouthi" value="bedouthi_sample" compare="diff" lines_diff="0"/>
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107 <output name="bedoutlo" value="bedoutlo_sample" compare="diff" lines_diff="0"/>
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108 <output name="tableoutfile" value="table_sample" compare="diff" lines_diff="0"/>
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109 <param name="outbeds" value="outlohi"/>
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110 <param name="bigwig" value="bigwig_sample"/>
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111 <param name="minwin" value="10"/>
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112 <param name="qhi" value="0.99"/>
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113 <param name="qlo" value="0.01"/>
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114 <param name="tableout" value="create"/>
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115 </test>
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116 <test expect_num_outputs="4">
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117 <output name="bedouthilo" value="bedouthilo2_sample" compare="diff" lines_diff="0"/>
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118 <output name="bedoutlo" value="bedoutlo2_sample" compare="diff" lines_diff="0"/>
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119 <output name="bedouthi" value="bedouthi2_sample" compare="diff" lines_diff="0"/>
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120 <output name="tableoutfile" value="table2_sample" compare="diff" lines_diff="0"/>
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121 <param name="outbeds" value="outall"/>
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122 <param name="bigwig" value="bigwig_sample,1.bigwig"/>
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123 <param name="minwin" value="10"/>
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124 <param name="qhi" value="0.99"/>
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125 <param name="qlo" value="0.01"/>
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126 <param name="tableout" value="create"/>
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127 </test>
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128 </tests>
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129 <help><![CDATA[
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130
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131 **Purpose**
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132
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133 *Combine bigwig outlier regions into bed files*
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134
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135 Bigwigs allow quantative tracks to be viewed in an interactive genome browser like JBrowse2.
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136 Peaks are easy to see. Unusually low regions can be harder to spot, even if they are relatively large, unless the view is zoomed right in.
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137 Automated methods for combining evidence from multiple bigwigs can be useful for constructing browseable *issues* or other kinds of summary bed format tracks.
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138 For example, combining coverage outlier regions, with the frequency of specific dicnucleotide short tandem repeats,
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139 for evaluating technical sequencing technology effects in the evaluation of a genome assembly described at https://github.com/arangrhie/T2T-Polish
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140
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141 **What does it produce?**
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142
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143 Bed format results are output, containing each continuous segment of at least *minwin* base pairs above a cut point, or below another cut point.
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144 These can be viewed as features on the reference genome using a genome browser tool like JBrowse2.
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145 Three kinds of bed files can be created depending on the values included.
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146 Both high and low regions in one bed output is the default. This can be displayed in JBrowse2 with colour indicating the high or low status,
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147 one less track and a little easier to understand. High and low features can be output as separate bed files.
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148
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149 **How is it controlled?**
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150
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151 The cut points are calculated using a user supplied quantile, from each chromosome's bigwig value distribution.
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152 The defaults are 0.99 and 0.01 and the default *minwin* is 10.
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153 The probability of 10 values at or below the 1st percentile purely by chance is about 0.01**10, so false positives should be
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154 rare, even in a 3GB genome.
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155 This data driven and non-parametric method is preferred for the asymmetrical distributions found in typical bigwigs, such as depth of coverage
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156 for genome sequencing reads. Coverage values are truncated at zero, and regions with very high values often form a long sparse right tail.
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157
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158 **How do I choose the input data?**
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159
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160 One or more bigwigs and can be selected as inputs.
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161 Multiple bigwigs will be combined in bed files, so must share the reference genome to display
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162 using JBrowse2.
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163
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164 .. class:: warningmark
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165
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166 **Lower quantile may not behave as expected in bigwigs with large fractions of zero values**
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167
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168 The lower cut point may be problematic for integer values like coverage if many values are zero. For example, if 5% of bases have zero coverage, the 1st percentile is also zero,
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169 but that cut point will include the entire 5% *at or below 0*
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170
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171
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172 ]]></help>
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173 <citations>
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174 <citation type="doi">10.1093/bioinformatics/btae350</citation>
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175 </citations>
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176 </tool>
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177