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"planemo upload for repository https://gitlab.com/paulklemm_PHD/proteinortho commit 95f1ae4ed1cdd56114df76d215f9e1ed549aa4c5"
author | iuc |
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date | Tue, 14 Sep 2021 11:39:10 +0000 |
parents | 4850f0d15f01 |
children | a8addd4fb60a |
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<tool id="proteinortho" name="Proteinortho" version="@TOOL_VERSION@+galaxy@WRAPPER_VERSION@" profile="@PROFILE@"> <description>detects orthologous proteins/genes within different species</description> <macros> <import>proteinortho_macros.xml</import> <xml name="test_outputs"> <output name="proteinortho"> <assert_contents> <has_line_matching expression="# Species\tGenes\tAlg\.-Conn\.\t.*"/> <has_line_matching expression="[0-9]+\t[0-9]+\t.*"/> <has_line_matching expression=".*(C|C2|E|L|M)_[0-9]+.*"/> </assert_contents> </output> <output name="blastgraph"> <assert_contents> <has_line_matching expression="# file_a\tfile_b"/> <has_line_matching expression="# a\tb\tevalue_ab\tbitscore_ab\tevalue_ba\tbitscore_ba"/> <has_line_matching expression="# (C|C2|E|L|M)\.fasta\t(C|C2|E|L|M)\.fasta"/> <has_line_matching expression=".*(C|C2|E|L|M)_[0-9]+\t(C|C2|E|L|M)_[0-9]+.*"/> </assert_contents> </output> <output name="proteinorthograph"> <assert_contents> <has_line_matching expression="# file_a\tfile_b"/> <has_line_matching expression="# a\tb\tevalue_ab\tbitscore_ab\tevalue_ba\tbitscore_ba(\tsame_strand\tsimscore)?"/> <has_line_matching expression="# (C|C2|E|L|M)\.fasta\t(C|C2|E|L|M)\.fasta"/> <has_line_matching expression=".*(C|C2|E|L|M)_[0-9]+\t(C|C2|E|L|M)_[0-9]+.*"/> </assert_contents> </output> </xml> </macros> <expand macro="requirements"/> <expand macro="version_command"/> <command detect_errors="exit_code"><![CDATA[ ## the following ln-action is necessary, since the file names are used by proteinortho (output contains filenames => species names) #import re #for $f in $input_files# ln -sf '$f' '${re.sub('[^\w\-_.]', '_', f.element_identifier)}' && #end for #if $synteny.synteny_options == "specified": #for $f in $synteny.input_files_syn# ln -sf '$f' '${re.sub('[^\w\-_.]', '_', f.element_identifier)}' && #end for# #end if proteinortho --project=result --cpus="\${GALAXY_SLOTS:-4}" --ram="\${GALAXY_MEMORY_MB:-16000}" #if $more_options.selfblast: $more_options.selfblast #end if #if $more_options.singles: $more_options.singles #end if --p=$p --e=$evalue #if $more_options.cov: --cov=$more_options.cov #end if #if $more_options.sim: --sim=`LC_NUMERIC=C awk "BEGIN {printf \"%.2f\",$more_options.sim/100}"` #end if #if $more_options.identity: --cov=$more_options.identity #end if #if $more_options.isoform != "no": --isoform=$more_options.isoform #end if #if $synteny.synteny_options == "specified": --synteny --dups=$synteny.dups --cs=$synteny.cs --alpha=$synteny.alpha #end if #for $f in $input_files# ${re.sub('[^\w\-_.]', '_', f.element_identifier)} #end for# #if $synteny.synteny_options == "specified": #for $f in $synteny.input_files_syn# ${re.sub('[^\w\-_.]', '_', f.element_identifier)} #end for# #end if 2> >(sed -E "s/.\[([0-9]{1,2}(;[0-9]{1,2})?)?[mGK]//g" 1>&2) #if $synteny.synteny_options == "specified": && mv result.poff-graph result.proteinortho-graph && mv result.poff.tsv result.proteinortho.tsv && mv result.poff.html result.proteinortho.html ; #end if ]]></command> <inputs> <param name="input_files" format="fasta" type="data" multiple="true" min="2" label="Select the input fasta files (>2)" help="The input fasta files. At least 2 are needed!"/> <param argument="--p" type="select" label="Similarity comparision algorithm" help="In the first step of proteinortho an all-versus-all reciprocal best hit graph is build from the input files (using this algorithm)."> <option value="diamond" selected="true">diamond (aminoacid sequences)</option> <option value="autoblast">auto detect NCBI-BLAST (protein and nucleotide sequences)</option> <option value="blastp">NCBI-BLASTP+ (protein sequences)</option> <option value="blastn">NCBI-BLASTN+ (nucleotide sequences)</option> <option value="lastp">Last (aminoacid sequences)</option> <option value="lastn">Last (nucleotide sequences)</option> <option value="blatp">BLAT (aminoacid sequences)</option> <option value="blatn">BLAT (nucleotide sequences)</option> </param> <param argument="--evalue" type="float" value="0.001" min="0" label="E-value threshold of the blast algorithm" help="This is the main parameter for the generation of the reciprocal best hit graph. Larger values results in more false positives (connections between proteins)."/> <param argument="--conn" type="float" value="0.1" min="0." max="10." label="Minimal algebraic connectivity" help="This is the main parameter for the clustering step. Choose larger values then more splits are done, resulting in more and smaller clusters."/> <section name="more_options" title="Additional Options" expanded="False"> <param argument="--cov" type="integer" value="50" min="0" max="100" label="Minimal coverage of best blast alignments in %"/> <param argument="--sim" type="integer" value="95" min="0" max="100" label="Minimal sequence similarity in %"/> <param argument="--identity" type="integer" value="25" min="0" max="100" label="Minimal percent identity of best blast hits in %"/> <param argument="--selfblast" type="boolean" checked="false" truevalue="--selfblast" falsevalue="" label="Apply selfblast, detects paralogs without orthologs "/> <param argument="--singles" type="boolean" checked="false" truevalue="--singles" falsevalue="" label="Report singleton genes without any hit "/> <param argument="--isoform" type="select" label="Use isoform information" help="The reciprocal best hit graph is build using isoform information (isoforms are treated equivalent). For ncbi : simply add the additional files to the input (file names need to match). For uniprot : the isoforms need to contain the word isoform and the corresponding identifier. For trinity simply use the trinity output format."> <option value="no" selected="true">Don't use isoform information</option> <option value="ncbi">ncbi style (..._additional.fasta)</option> <option value="uniprot">uniprot style (...isoform of...)</option> <option value="trinity">trinity style (...i4)</option> </param> </section> <conditional name="synteny"> <param name="synteny_options" type="select" label="Activate synteny feature (POFF)" help="To enhance the prediction accuracy, the relative order of genes (synteny) can be used as additional feature for the discrimination of orthologs. For more details see doi:10.1371/journal.pone.0105015."> <option value="no" selected="true">no</option> <option value="specified">yes</option> </param> <when value="no"/> <when value="specified"> <param argument="--dups" type="integer" value="0" min="0" max="100" label="Number of reiterations for adjacencies heuristic, to determine duplicated regions"/> <param argument="--cs" type="integer" value="3" min="0" max="100" label="Size of a maximum common substring (MCS) for adjacency matches"/> <param argument="--alpha" type="float" value="0.5" min="0." max="1." label="Minimal percent identity of best blast hits"/> <param name="input_files_syn" type="data" format="gff" multiple="true" min="2" label="Select the GFF3 files matching the input fasta files" help="The GFF3 files need matching names with the input fasta files. If you provide mybacteria123.faa or mybacteria123.fasta ... then you need to provide mybacteria123.gff here accoringly. The attributes column (#9) must contain the attribute Name=GENE IDENTIFIER where GENE IDENTIFIER corresponds to the respective (protein) identifier in the FASTA input. For example see https://gitlab.com/paulklemm_PHD/proteinortho/-/blob/master/test/C.gff"/> </when> </conditional> </inputs> <outputs> <data name="blastgraph" format="tabular" label="${tool.name} on ${on_string}: RBH graph" from_work_dir="result.blast-graph"/> <data name="proteinortho" format="tabular" label="${tool.name} on ${on_string}: orthology-groups" from_work_dir="result.proteinortho.tsv"/> <data name="proteinorthograph" format="tabular" label="${tool.name} on ${on_string}: orthology-pairs" from_work_dir="result.proteinortho-graph"/> </outputs> <tests> <test expect_num_outputs="3"> <!-- test normal --> <param name="input_files" value="L.fasta,C.fasta,C2.fasta,E.fasta,M.fasta"/> <expand macro="test_outputs"/> <assert_command> <has_text text="--p=diamond"/> </assert_command> </test> <test expect_num_outputs="3"> <!-- various parameter --> <param name="input_files" value="L.fasta,C.fasta,C2.fasta,E.fasta,M.fasta"/> <param name="evalue" value="1"/> <param name="conn" value="1"/> <param name="cov" value="42"/> <param name="sim" value="42"/> <param name="identity" value="42"/> <param name="selfblast" value="true"/> <param name="singles" value="true"/> <expand macro="test_outputs"/> <assert_command> <has_text text="--p=diamond"/> </assert_command> </test> <test expect_num_outputs="3"> <!-- synteny --> <param name="input_files" value="L.fasta,C.fasta,C2.fasta,E.fasta,M.fasta"/> <param name="input_files_syn" value="L.gff,C.gff,C2.gff,E.gff,M.gff"/> <param name="synteny_options" value="specified"/> <expand macro="test_outputs"/> <assert_command> <has_text text="--p=diamond"/> </assert_command> </test> <test expect_num_outputs="3"> <!-- blast --> <param name="input_files" value="L.fasta,C.fasta,C2.fasta,E.fasta,M.fasta"/> <param name="p" value="blastp"/> <expand macro="test_outputs"/> <assert_command> <has_text text="--p=blastp"/> </assert_command> </test> <test expect_num_outputs="3"> <!-- auto blast --> <param name="input_files" value="L.fasta,C.fasta,C2.fasta,E.fasta,M.fasta"/> <param name="p" value="autoblast"/> <expand macro="test_outputs"/> <assert_command> <has_text text="--p=autoblast"/> </assert_command> </test> <test expect_num_outputs="3"> <!-- last --> <param name="input_files" value="L.fasta,C.fasta,C2.fasta,E.fasta,M.fasta"/> <param name="p" value="lastp"/> <expand macro="test_outputs"/> <assert_command> <has_text text="--p=lastp"/> </assert_command> </test> <test expect_num_outputs="3"> <!-- blat --> <param name="input_files" value="L.fasta,C.fasta,C2.fasta,E.fasta,M.fasta"/> <param name="p" value="blastp"/> <expand macro="test_outputs"/> <assert_command> <has_text text="--p=blastp"/> </assert_command> </test> </tests> <help><![CDATA[Proteinortho with POFF - An orthology detection tool **What it does** Proteinortho is a tool to detect orthologous proteins/genes within different species (at least 2). | It compares similarities of given gene/protein sequences and clusters them to find significant groups. | The algorithm was designed to handle large-scale data and can be applied to hundreds of species at one. | Details can be found in (doi:10.1186/1471-2105-12-124). | To enhance the prediction accuracy, the relative order of genes (synteny) can be used as additional feature for the discrimination of orthologs. The corresponding extension, namely PoFF (details see doi:10.1371/journal.pone.0105015), is already build in Proteinortho. ---- **Proteinortho in a nutshell** ---- * **(i) Build adaptive reciprocal best hit graph (RBH)** | Using the blast algorithm (diamond,blast,blat,...) all input sequences are compared against each other. | If two proteins find each other with respect to multiple criteria like minimal evalue, similarity compared to the best hit, ... then a edge is drawn between the two proteins. | The result of this step is outputted to RBH * **(ii) Cluster the RBH** | Using two clustering algorithms, edges are removed that weakly connect two connected components to reduce false positive hits. | The resulting connected components are outputted in orthology-groups / -PAIRS ---- **Proteinortho output files** ---- * **RBH** | The result of the (i) step, the reciprocal best hit graph. | First a comment line announces 2 species (# ecoli.faa human.faa), then each line corresponds to a reciprocal best hit between 2 proteins/genes of the announced species. The output format is shown below. | *seqidA*,*seqidB* = the 2 ids/names of the proteins involved | *evalue_ab* = evalue with seqidA as query and seqidB as part of the database | *bitscore_ab* = bitscore with seqidA as query ... | *evalue_ba* = evalue with seqidB as query ... | ... .. csv-table:: seqidA,seqidB,evalue_ab,bitscore_ab,evalue_ba,bitscore_ba ---- * **orthology-groups** | The result of the (ii) step, the clustered reciprocal best hit graph or the orthology groups. | Every line corresponds to an orthology group of proteins/genes. | The first 3 columns characterize general properties of that group: number of proteins, species and the algebraic connectivity. The higher the algebraic connectivity the more edges are there and the better the group is connected to itself in general. | Then a column for each species follows containing the proteins of that species. If a species contributes with more than one protein to a group of orthologs, then they are ordered by connectivity. .. csv-table:: Species,Genes,Alg.-Conn. ---- * **orthology-pairs** | The same as orthology-groups but every edge is printed one-by-one here. The output is formatted the same as the RBH graph: .. csv-table:: seqidA,seqidB,evalue_ab,bitscore_ab,evalue_ba,bitscore_ba ---- **Proteinortho-Tools for downstream analysis** * `proteinortho grab proteins` : find gene(s)/protein(s) in a given fasta file and retrieve their sequence(s). You can also use a orthology-groups file. * `proteinortho summary` : Summaries the orthology-pairs/RBH files to determine how the species are connected to each other. More information can be found on github https://gitlab.com/paulklemm_PHD/proteinortho ]]> </help> <expand macro="citations"/> </tool>