Mercurial > repos > peterjc > tmhmm_and_signalp

annotate tools/protein_analysis/rxlr_motifs.xml @ 18:2b35b5c4b7f4 draft

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Uploaded v0.2.5, preview 2, fixed bug in RXLR tools
author peterjc
date Fri, 10 May 2013 07:48:26 -0400
parents af3174637834
children a538e182fab3
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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 clevage 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 clevage 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 clevage 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 clevage 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 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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139 A translocation signal for delivery of oomycete effector proteins into host plant cells.
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140 Nature 450:115-118, 2007.
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141 http://dx.doi.org/10.1038/nature06203
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142
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143 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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144 Adaptive evolution has targeted the C-terminal domain of the RXLR effectors of plant pathogenic oomycetes.
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145 The Plant Cell 19:2349-2369, 2007.
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146 http://dx.doi.org/10.1105/tpc.107.051037
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147
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148 Souvik Bhattacharjee, N. Luisa Hiller, Konstantinos Liolios, Joe Win, Thirumala-Devi Kanneganti, Carolyn Young, Sophien Kamoun and Kasturi Haldar.
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149 The malarial host-targeting signal is conserved in the Irish potato famine pathogen.
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150 PLoS Pathogens, 2(5):e50, 2006.
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151 http://dx.doi.org/10.1371/journal.ppat.0020050
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152
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153 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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154 EST mining and functional expression assays identify extracellular effector proteins from the plant pathogen *phytophthora*.
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155 Genome Research, 13:1675-1685, 2003.
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156 http://dx.doi.org/10.1101/gr.910003
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157
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158 Sean R. Eddy.
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159 Profile hidden Markov models.
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160 Bioinformatics, 14(9):755–763, 1998
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161 http://dx.doi.org/10.1093/bioinformatics/14.9.755
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162
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163 Nielsen, Engelbrecht, Brunak and von Heijne.
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164 Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.
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165 Protein Engineering, 10:1-6, 1997.
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166 http://dx.doi.org/10.1093/protein/10.1.1
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167
17
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168 This wrapper is available to install into other Galaxy Instances via the Galaxy
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169 Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp
6
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170 </help>
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171 </tool>