Mercurial > repos > peterjc > tmhmm_and_signalp

annotate tools/protein_analysis/rxlr_motifs.xml @ 21:4cee8236c77b draft

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Uploaded v0.2.5 preview 5, adopt standard MIT licence.
author peterjc
date Tue, 10 Sep 2013 09:02:05 -0400
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17
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1 <tool id="rxlr_motifs" name="RXLR Motifs" version="0.0.7">
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2 <description>Find RXLR Effectors of Plant Pathogenic Oomycetes</description>
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3 <command interpreter="python">
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4 rxlr_motifs.py $fasta_file 8 $model $tabular_file
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5 ##I want the number of threads to be a Galaxy config option...
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6 </command>
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7 <stdio>
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8 <!-- Anything other than zero is an error -->
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9 <exit_code range="1:" />
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10 <exit_code range=":-1" />
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11 </stdio>
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12 <inputs>
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13 <param name="fasta_file" type="data" format="fasta" label="FASTA file of protein sequences" />
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14 <param name="model" type="select" label="Which RXLR model?">
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15 <option value="Bhattacharjee2006">Bhattacharjee et al. (2006) RXLR</option>
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16 <option value="Win2007">Win et al. (2007) RXLR</option>
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17 <option value="Whisson2007" selected="True">Whisson et al. (2007) RXLR-EER with HMM</option>
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18 </param>
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19 </inputs>
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20 <outputs>
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21 <data name="tabular_file" format="tabular" label="$model.value_label" />
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22 </outputs>
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23 <requirements>
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24 <!-- Need SignalP for all the models -->
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25 <requirement type="binary">signalp</requirement>
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26 <!-- Need HMMER for Whisson et al. (2007) -->
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27 <requirement type="binary">hmmsearch</requirement>
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28 </requirements>
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29 <tests>
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30 <test>
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31 <param name="fasta_file" value="rxlr_win_et_al_2007.fasta" ftype="fasta" />
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32 <param name="model" value="Win2007" />
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33 <output name="tabular_file" file="rxlr_win_et_al_2007.tabular" ftype="tabular" />
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34 </test>
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35 <test>
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36 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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37 <param name="model" value="Bhattacharjee2006"/>
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38 <output name="tabular_file" file="empty_rxlr.Bhattacharjee2006.tabular" ftype="tabular"/>
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39 </test>
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40 <test>
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41 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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42 <param name="model" value="Win2007"/>
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43 <output name="tabular_file" file="empty_rxlr.Win2007.tabular" ftype="tabular"/>
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44 </test>
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45 <test>
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46 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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47 <param name="model" value="Whisson2007"/>
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48 <output name="tabular_file" file="empty_rxlr.Whisson2007.tabular" ftype="tabular"/>
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49 </test>
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50 </tests>
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51 <help>
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52
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53 **Background**
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54
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55 Many effector proteins from oomycete plant pathogens for manipulating the host
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56 have been found to contain a signal peptide followed by a conserved RXLR motif
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57 (Arg, any amino acid, Leu, Arg), and then sometimes EER (Glu, Glu, Arg). There
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58 are striking parallels with the malarial host-targeting signal (Plasmodium
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59 export element, or "Pexel" for short).
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60
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61 -----
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62
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63 **What it does**
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64
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65 Takes a protein sequence FASTA file as input, and produces a simple tabular
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66 file as output with one line per protein, and two columns giving the sequence
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67 ID and the predicted class. This is typically just whether or not it had the
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68 selected RXLR motif (Y or N).
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69
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70 -----
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71
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72 **Bhattacharjee et al. (2006) RXLR Model**
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73
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74 Looks for the oomycete motif RXLR as described in Bhattacharjee et al. (2006).
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75
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76 Matches must have a SignalP Hidden Markov Model (HMM) score of at least 0.9,
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77 a SignalP Neural Network (NN) predicted cleavage site giving a signal peptide
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78 length between 10 and 40 amino acids inclusive, and the RXLR pattern must be
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79 after but within 100 amino acids of the cleavage site.
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80 SignalP is run truncating the sequences to the first 70 amino acids, which was
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81 the default on the SignalP webservice used in Bhattacharjee et al. (2006).
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82
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83
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84 **Win et al. (2007) RXLR Model**
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85
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86 Looks for the protein motif RXLR as described in Win et al. (2007).
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87
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88 Matches must have a SignalP Hidden Markov Model (HMM) score of at least 0.9,
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89 a SignalP Neural Network (NN) predicted cleavage site giving a signal peptide
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90 length between 10 and 40 amino acids inclusive, and the RXLR pattern must be
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91 after the cleavage site and start between amino acids 30 and 60.
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92 SignalP is run truncating the sequences to the first 70 amino acids, to match
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93 the methodology of Torto et al. (2003) followed in Win et al. (2007).
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94
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95
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96 **Whisson et al. (2007) RXLR-EER with HMM**
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97
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98 Looks for the protein motif RXLR-EER using the heuristic regular expression
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99 methodolgy, which was an extension of the Bhattacharjee et al. (2006) model,
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100 and a HMM as described in Whisson et al. (2007).
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101
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102 All the requirements described above for Bhattacharjee et al. (2006) apply,
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103 but rather than just looking for RXLR with the regular expression R.LR the
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104 more complicated regular expression R.LR.{,40}[ED][ED][KR] is used. This means
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105 RXLR (Arg, any amino acid, Leu, Arg), then a stretch of up to forty amino
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106 acids before Glu/Asp, Glu/Asp, Lys/Arg. The EER part of the name is perhaps
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107 misleading as it also allows for DDR, EEK, and so on.
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108
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109 Unlike Bhattacharjee et al. (2006) which used the SignalP webservice which
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110 defaults to truncating the sequences at 70 amino acids, Whisson et al. (2007)
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111 used the SignalP 3.0 command line tool with its default of not truncating the
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112 sequences. This does alter some of the scores, and also takes a little longer.
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113
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114 Additionally HMMER 2.3.2 is run to look for a cross validated HMM for the
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115 RXLR-ERR domain based on known positive examples. There are no restrictions
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116 on where within the protein the HMM match must be found.
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117
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118 The output of this model has four classes:
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119 * Y = Yes, both the heuristic motif and HMM were found.
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120 * re = Only the heuristic SignalP with regular expression motif was found.
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121 * hmm = Only the HMM was found.
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122 * neither = Niether the heuristic motif nor HMM was found.
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123
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124 -----
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125
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126 **Note**
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127
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128 Both Bhattacharjee et al. (2006) and Win et al. (2007) used SignalP v2.0, which
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129 is no longer available. The current release is SignalP v3.0 (Mar 5, 2007), so
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130 this is used instead. SignalP is called with the Eukaryote model and the short
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131 output (one line per protein). Any sequence truncation (e.g. to 70 amino acids)
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132 is handled via the intemediate sequence files.
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133
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134 -----
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135
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136 **References**
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137
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138 If you use this Galaxy tool in work leading to a scientific publication please
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139 cite Cock et al. (2013) and the appropriate method paper(s):
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140
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141 Peter Cock, Bjoern Gruening, Konrad Paszkiewicz and Leighton Pritchard (2013).
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142 Galaxy tools and workflows for sequence analysis with applications
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143 in molecular plant pathology. PeerJ 1:e167
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144 http://dx.doi.org/10.7717/peerj.167
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145
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146 Stephen C. Whisson, Petra C. Boevink, Lucy Moleleki, Anna O. Avrova, Juan G. Morales, Eleanor M. Gilroy, Miles R. Armstrong, Severine Grouffaud, Pieter van West, Sean Chapman, Ingo Hein, Ian K. Toth, Leighton Pritchard and Paul R. J. Birch
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147 A translocation signal for delivery of oomycete effector proteins into host plant cells.
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148 Nature 450:115-118, 2007.
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149 http://dx.doi.org/10.1038/nature06203
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150
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151 Joe Win, William Morgan, Jorunn Bos, Ksenia V. Krasileva, Liliana M. Cano, Angela Chaparro-Garcia, Randa Ammar, Brian J. Staskawicz and Sophien Kamoun.
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152 Adaptive evolution has targeted the C-terminal domain of the RXLR effectors of plant pathogenic oomycetes.
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153 The Plant Cell 19:2349-2369, 2007.
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154 http://dx.doi.org/10.1105/tpc.107.051037
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155
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156 Souvik Bhattacharjee, N. Luisa Hiller, Konstantinos Liolios, Joe Win, Thirumala-Devi Kanneganti, Carolyn Young, Sophien Kamoun and Kasturi Haldar.
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157 The malarial host-targeting signal is conserved in the Irish potato famine pathogen.
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158 PLoS Pathogens, 2(5):e50, 2006.
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159 http://dx.doi.org/10.1371/journal.ppat.0020050
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160
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161 Trudy A. Torto, Shuang Li, Allison Styer, Edgar Huitema, Antonino Testa, Neil A.R. Gow, Pieter van West and Sophien Kamoun.
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162 EST mining and functional expression assays identify extracellular effector proteins from the plant pathogen *phytophthora*.
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163 Genome Research, 13:1675-1685, 2003.
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164 http://dx.doi.org/10.1101/gr.910003
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165
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166 Sean R. Eddy.
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167 Profile hidden Markov models.
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168 Bioinformatics, 14(9):755–763, 1998
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169 http://dx.doi.org/10.1093/bioinformatics/14.9.755
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170
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171 Nielsen, Engelbrecht, Brunak and von Heijne.
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172 Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.
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173 Protein Engineering, 10:1-6, 1997.
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174 http://dx.doi.org/10.1093/protein/10.1.1
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175
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176 This wrapper is available to install into other Galaxy Instances via the Galaxy
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177 Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp
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178 </help>
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179 </tool>