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1 <tool id="sam_header" name="NGS Run Annotation">
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2 <description>Create a SAM format header from run metadata for sample annotation.</description>
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3 <requirements>
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4 <requirement type="package" version="3.4.1">python3</requirement>
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5 <requirement type="package" version="0.1.3_9af04e0e9125">MiModD</requirement>
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6 </requirements>
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7 <command>
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8 mimodd header
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9
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10 --rg_id "$rg_id"
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11 --rg_sm "$rg_sm"
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12
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13 #if $str($rg_cn):
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14 --rg_cn "$rg_cn"
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15 #end if
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16 #if $str($rg_ds):
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17 --rg_ds "$rg_ds"
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18 #end if
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19 #if $str($anno) and $str($month) and $str($day):
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20 --rg_dt "$anno-$month-$day"
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21 #end if
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22 #if $str($rg_lb):
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23 --rg_lb "$rg_lb"
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24 #end if
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25 #if $str($rg_pl):
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26 --rg_pl "$rg_pl"
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27 #end if
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28 #if $str($rg_ds):
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29 --rg_pi "$rg_pi"
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30 #end if
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31 #if $str($rg_pu):
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32 --rg_pu "$rg_pu"
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33 #end if
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34
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35 --outputfile $outputfile
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36
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37 </command>
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38
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39 <inputs>
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40 <param name="rg_id" type="text" size="80" label="read-group ID (mandatory)">
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41 <sanitizer invalid_char="">
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42 <valid initial="string.printable">
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43 <remove value=""" />
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44 </valid>
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45 <mapping initial="none">
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46 <add source=""" target="\""/>
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47 </mapping>
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48 </sanitizer>
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49 </param>
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50 <param name="rg_sm" type="text" size="80" label="sample name (mandatory)">
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51 <sanitizer invalid_char="">
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52 <valid initial="string.printable">
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53 <remove value=""" />
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54 </valid>
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55 <mapping initial="none">
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56 <add source=""" target="\""/>
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57 </mapping>
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58 </sanitizer>
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59 </param>
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60 <param name="rg_cn" type="text" size="80" label="name of sequencing center">
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61 <sanitizer invalid_char="">
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62 <valid initial="string.printable">
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63 <remove value=""" />
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64 </valid>
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65 <mapping initial="none">
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66 <add source=""" target="\""/>
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67 </mapping>
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68 </sanitizer>
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69 </param>
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70 <param name="rg_ds" type="text" size="80" label="description">
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71 <sanitizer invalid_char="">
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72 <valid initial="string.printable">
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73 <remove value=""" />
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74 </valid>
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75 <mapping initial="none">
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76 <add source=""" target="\""/>
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77 </mapping>
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78 </sanitizer>
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79 </param>
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80 <param name="anno" type="text" label="year (YYYY) the run was produced" />
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81 <param name="month" type="text" label="month (MM) the run was produced" />
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82 <param name="day" type="text" label="day (DD) the run was produced" />
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83 <param name="rg_lb" type="text" size="80" label="read-group library">
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84 <sanitizer invalid_char="">
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85 <valid initial="string.printable">
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86 <remove value=""" />
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87 </valid>
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88 <mapping initial="none">
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89 <add source=""" target="\""/>
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90 </mapping>
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91 </sanitizer>
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92 </param>
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93 <param name="rg_pl" type="text" label="platform/technology used to produce the reads" />
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94 <param name="rg_pi" type="text" label="predicted median insert size" />
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95 <param name="rg_pu" type="text" size="80" label="platform unit; unique identifier">
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96 <sanitizer invalid_char="">
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97 <valid initial="string.printable">
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98 <remove value=""" />
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99 </valid>
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100 <mapping initial="none">
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101 <add source=""" target="\""/>
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102 </mapping>
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103 </sanitizer>
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104 </param>
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105 </inputs>
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106
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107 <outputs>
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108 <data name="outputfile" format="sam" label="${rg_sm} (${rg_id}) header information from MiModd ${tool.name} on ${on_string}"/>
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109 </outputs>
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110
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111 <help>
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112 .. class:: infomark
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113
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114 **What it does**
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115
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116 This tool takes the user-provided information about a next-generation sequencing run and constructs a valid header in the SAM file format from it.
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117
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118 The result file can be used by the tools *Convert* and *Reheader* or in the *SNAP Read Alignment* step to add run metadata to sequenced reads files (or to overwrite pre-existing information).
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119
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120 **Note:**
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121
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122 **MiModD requires run metadata for every input file at the Alignment step !**
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123
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124 **Tip:**
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125
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126 While you can do Alignments from fastq file format by providing a custom header file directly to the *SNAP Read Alignment* tool, the **recommended approach** is to first convert all input files to and archive all datasets in SAM/BAM format with appropriate header information prior to any downstream analysis. Although a bit more time-consuming this practice protects against information loss and ensures that the input datasets will remain useful for others in the future.
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127
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128 </help>
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129 </tool>
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130
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