OrthoSelect User Guide
Contents
1. 002 NOISY ee ae pia ee ew a aA 7 0 3 _AliScore 2 o a aa a a a a E 8 Short Version An Example Analysis 1 1 Install external programs 8 2 3 Final preparation 8 3 Orthology Assignment 9 Troubleshooting 9 1 Error Messages ssaa aaia a a ee A Format required_taxa_list txt 8 1 2 Fasta files ooa a 8 2 Prepare Analysis oaoa 02 eee ee 8 2 1 Configuration File 2 0 2 0 0 0000 8 2 2 Selection of ortholog database 20 8 5 Eliminating Redundancies 000 4 8 6 Alignment Curation 2 2 0 0 0 02000 10 10 10 10 11 11 11 11 13 14 16 16 17 19 21 22 23 23 25 25 25 25 26 26 27 27 28 28 29 30 30 32 B Format taxa_list txt 32 32 C 1 dbEST Option s n o a 00 2000008 32 C 2 TBestDB Option s d 2 2 0 0 0002000 32 C 3 JGI ESTs Option se 2 2 00 02 0202002 32 C 4 JGI transcripts Option s t 2 2 2 0 2 2000 33 D Fasta Conversions Batch mode 33 E Overview One letter functional classification used in the KOG 33 F Format options_ txt 35 1 Introduction DNA and protein sequences provide a wealth of information which is routinely used in phylogenetic studies Traditionally single genes or small groups of genes have been used to infer the phylogeny of a group of species under study It has been2. Annotations are saved in root_path TEST_ANALYSIS annotations This folder will now contain the annotation for all our taxa in the study The folder comprises Aspergillus_niger txt Ciona_intestinalis txt Daphnia_pulex txt Lottia_gigantea txt Monosiga_brevicollis txt 27 8 4 Gene Selection Now we may want to reduce the dataset to include only OGs with our species of interest present The selection of OGs will be according to the existence of at least one sequence for each of the following species Aspergillus niger and Daphnia pulex We simply copy the file containing all taxa in the study taxa_list txt by de fault delete all unwanted lines and save the file under required_taxa_list txt The file then looks like this Aspergillus_niger Aspergi_ni Daphnia_pulex Daphnia_pu Since we are using default settings we do not need to change the configuration file We start this part of the analysis by typing perl perl_scripts gene_selection pl The folder root_path TEST_ANALYSIS selected_genes will contain then the following OGs K0G0019 KOGO020 KQ0QGO0027 K0G0179 K0G0213 8 5 Eliminating Redundancies So far our OGs contain homologous sequences that are orthologs and paralogs but we want to keep the orthologs only The selected target genes are in the directory selected_genes and we want the results of this step of the analysis to be saved in the new folder reduced_genes The dis
3. home user orthoselect needs to be replaced by the path OrthoS elect is installed in This path will be known as root_path from now on 8 2 2 Selection of ortholog database We decide to use the KOG database Therefore we mark the corresponding option in the configuration file orthology_database_type k 26 8 2 3 Final preparation To automatically download format and test the ortholog database as well as to perform some final tests we call the perl script prepare_analysis pl as follows perl perl_scripts prepare_analysis pl 8 3 Orthology Assignment Now we want to assign orthology to our EST sequences in folder root_path est_libraries Using default settings in the configuration file we start the analysis on our single computer by typing perl perl_scripts start_orthology_assignment_single pl After the analysis has finished the project folder root_path TEST_ANALYSIS will contain the following directories annotations basis_hits The results have been saved to the folder root_path TEST_ANALYSIS basis_hits and contain the following OGs KOGO0O03 KO0GO019 KOGO020 KOGO027 KO0GO179 K0G0213 The EST sequence as well as its translation will be saved in the corresponding OG subfolder E g an EST sequence from Daphina_pulex assigned to KOG0213 will be saved as K0G0213_Daphnia_pulex_prot_hits fasta K0G0213_Daphnia_pulex_nucl_hits fasta in root_path TEST_ANALYSIS basis_hits KOG0213
4. taxa_conversion txt test_data Aspnil_FilteredModelsi na fasta Aspergillus_niger t test_data Cintestinals_EST_clusters fasta Ciona_intestinalis e test_data FrozenGeneCatalog_2007_07_03 na fasta Daphnia_pulex t test_data Lotgil_EstClusters_naClusterCr705LottiaJgi20060727 fasta Lottia_gigantea e test_data Monbri_ESTclusters fasta Monosiga_brevicollis e We convert the fasta headers in the correct format by typing perl perl_scripts fasta_header_converter pl The sequences with correct fasta headers will now be in the diretory est libraries that is the directory OrthoSelect looks for EST libraries The correct fasta head ers will then look like this File est_libraries Aspergillus_niger fa Header gt 202811 Aspergillus_niger File est_libraries Ciona_intestinalis fa Header gt 847937_2 Ciona_intestinalis File est_libraries Daphnia_pulex fa Header gt 48454 Daphnia_pulex File est_libraries Lottia_gigantea fa Header gt 4243977_1 Lottia_gigantea File est_libraries Monosiga_brevicollis fa Header gt 3716647_1 Monosiga_brevicollis 8 2 Prepare Analysis 8 2 1 Configuration File Now we have to tell the program the location where we installed OrthoSelect Furthermore we tell the program the name of our project All results will be saved in that project folder We adapt the configuration file as follows project_name TEST_ANALYSIS root_directory home user OrthoSelect The path
5. 6 2 Required external Programs The following external programs need to be installed on your system Download and install them Make sure that all programs are accessible from the command lind The tested versions of the program are in brackets e BioPerl Version 1 5 1 e BLAST Version 2 2 18 e ESTScan Version 2 2 1 e Wise Version 2 2 0 e HMMER Version 3 alpha e Clustalw Version 2 0 8 e T Coffee Version 5 72 or Muscle Version 3 7 e Gblocks Version 0 91b e Noisy Version 1 5 7P 6 3 Automatical download of required programs Alternatively you can use a script that automatically and installs all required programs The script has been tested with Macosx 10 5 2 Ubuntu 32 bit and the bash shell which is the default shell 1You can check this manually by entering the program name in the command line If the program starts it is installed and accessible if not then an error message with inform you 2Due to difficulties installing this software we do not offer to automatically install these software Nevertheless Noisy manually installed can be used by OrthoSelect 10 6 3 1 Start the automated download You can now start the script that automatically downloads and installs the missing required programs by typing perl perl_scripts auto_download pl o OS p t where OS can be replaced by macosx or linux if you want to install the programs on Macosx or Linux Set the parameter p
6. aligned protein the postfix prot_hits fasta and unaligned nucleotide sequences the postfix nucl_hits fasta 7 5 Alignment Curation The final part comprises the use of different algorithms to refine the alignment and improve the accuracy of the following phylogenetic reconstruction Since not all parts of a gene evolve at the same rate alignments can be composed of highly conserved and less conserved regions Useful regions for phylogenetic analysis are those that are conserved to a certain degree because either regions full of the identical characters or regions too divergent to be correctly aligned do not contain useful phylogenetic signal Note that the user is encouraged to manually check all alignments Since OrthoSelect selects that sequence from an organism most likely being an or tholog in Section 7 4 it can select paralogs in case orthologs are missing in the data or organism due to gene loss In case the alignment contains sequences that obviously do not fit in the alignment the user is encouraged to check the annotations as well as the nucleotide sequence of that sequences The following two programs try to select parts of the alignment suitable for phylogenetic analysis Gblocks and to eliminate potentially homoplastic sites Noisy Furthermore we implemented the tool Aliscore It maskes random sequence similarities in multiple sequence alignments 7 5 1 Gblocks Gblocks Castresana 2000 is a tool that auto
7. OGs with the est sequences assigned to it are in the subdirectory basis_hits of the project directory see Fig 4 for an overview Create statistic file After the orthology assignment the results folder will contain a lot of hits Given a list of taxa in the study e g taxa_list txt one want to know the distribution of hits for the different taxa and OGs A presence absence tab delimited text nd will be created for all taxa from taxa_list txt and OGs in the study The statistic can also be generated to a later point of the analysis For this you have to change the statistic_directory in the configuration file This text file can then be easily imported into spread sheet applications e g Excel Options Set the following options in the configuration file options txt by default statistic_directory basis_hits The statistic_directory is the directory containing the OGs to be analysed Perform Analysis Start the analysis by typing perl perl_scripts stats pl gt text file where text file will then contain the statistics text file can be replaced by any name to avoid to overwrite existing statistical files 15 presence of a species is coded as 1 absence as 0 17 Output By default the statistics will be stored in the file text file 18 7 3 Gene Selection Optional With assembled EST sequences assigned to predefined ortholog groups OG and translated into p
8. post_processing pl Output By default the results will be stored in the subfolder reduced_hits of the project folder The geblocked alignments will have the postfix gblocked fasta the alignments processed with noisy will have the postfix out fas Nosiy ad ditionally creates the files sta gr and typ eps Geblocked alignments with sequences filtered out have the postfix gblocked_filtered fasta The name and the percentage of character content of the sequences which have been filtered out are in the file LOG_rejected_sequences txt The alignments processed by AliScore have the postfix final_aliscore fasta 24 8 Short Version An Example Analysis This section is a quick guide to start the analysis For this purpose a test dataset will be included in the OrthoSelect download The dataset consists of orginal sequences downloaded from JGI The original dataset has been reduced to include only a few sequences from each taxon that will be assigned to the same ortholog groups For details and background please see the long version in section 6 8 1 Input Data 8 1 1 Install external programs After extracting OrthoSelect all missing required external programs as well as BioPerl will be downloaded and installed under linux typing perl perl_scripts auto_download pl o linux p t We re read the shell profile so that OrthoSelect can find all required programs and variables by typing sourc
9. project folder see Fig 4 for an overview Each OG contains the est se quence files with nucl and its translation files with prot with the name of the file corresponding to the taxon the sequence belong to The annotations can be found in the subfolder annotations of the project folder see Fig for an overview Annotation files contain the following information Identi fier in fasta file Taxon name Assigned OG one letter functional annotation Annotation E value of best hit Identifier of best hit of assigned OG Method used for translation E value for translation with GeneWise standard 6 frame translation and ESTScan by comparing the translated sequence with the best database hit using bl2seq E g Aspergi_ni ACC69732 Aspergillus_niger K0G4663 C Cytochrome b 3e 75 HsMi013 GeneWise 7e 83 2e 82 3e 27 Here the EST sequence with the accession number ACC69732 from the organ ism Aspergillus_niger was assigned to the OG KOG4663 a cytochrome b with an E value of 3e 75 The best hit was with the sequence HsMi013 and the se quence was translated using GeneWise since it produced the most significant translation E value 7e 83 The table containing the one letter functional clas sification used in the KOG database can either be found in file fun txt in the database directory see Fig 4 for an overview or in the appendix E 7 2 Statistics View results from orthology search As mentioned before the
10. shown however that molecular phylogenies based on single genes often lead to apparently conflicting tree hypotheses 2005 The combination of a large number of genes and species in genome scale approaches to reconstruct phylogenies can be useful to overcome these difficulties 2003 This approach has been termed phylogenomics Eisen 1998 Since complete genome sequences are available only for a limited number of species many phylogenomic studies rely on EST sequences EST sequences are short 200 800 bases unedited randomly selected single pass reads from cDNA libraries that sample the diversity of genes expressed by an organism or tissue at a particular time under particular conditions The relatively low cost and rapid generation of EST sequences can deliver insights into transcribed genes from a large number of taxa Moreover EST sequences contain a wealth of phylogenetic information Several recent phylogenomic studies used EST sequences to generate large data matrices Bourlat et al 2006 Delsuc et al 2006 2008 Such studies start with the generation of EST libraries for a set of species ESTs are then assembled and ortholog genes are identified as a basis for phylogenetic reconstruction Phylogenetically related sequences are called ortholog if they were separated by a speciation event as opposed to paralog sequences which were separated by a duplication event within the same species 1970 Orthologs are usually functiona
11. t if you also wish to install bioperl You can check whether you have bioperl installed or not by typing perl e use Bio Perl If this command results in an error message then bioperl is not yet installed on your system The script downloads and installs all required programs in the folder programs If you experience any problems try to install the program by using fink or darwinports or ask your local administrator All programs should be now installed on your computer In order for Or thoSelect to access all required programs the profile file needs to be re read by the shell To do this simply type source profile 6 4 User Input EST libraries 6 4 1 Where to put the EST libraries The EST libraries should be in fasta format Copy all EST libraries you want to analyse in the subfolder est_libraries of the folder where OrthoSelect has been installed see Fig 4 6 4 2 Adapting the fasta header of the EST libraries To guarantee a smoothly flow of the analysis the fasta file are required to meet the following two criteria Fasta header It is important that each EST sequence in a fasta file is dis tinguishable by a unique identifier e g an accession number OrthoSelect will use everything until the first blank as the accession number The following gt Accession_number WILL_BE_IGNORED E g gt id203335 SOME_ANNOTATION or gt id203335 Aspergillus_niger 3 All perl scripts wi
12. the following options in the configuration file options txt by default gene_selection_option m The selection of s corresponds to strategy 1 m to strategy 2 gene_selection_directory selected_genes required_taxa_file required_taxa_list txt The directory gene selection_directory will contain only those OGs selected by one of the search strategies The file required_taxa_file will contain the taxa upon which a selection of OGs will be made Depending on the selection criterion used the file should look as follows Strategy 1 The selection of those OGs according to the existence in at least one member of a pre defined monophyletic group The syntax of the file should be Name_for_monophylum Speciesi Species2 SpeciesxX eg Tetraconata Drosophila_melanogaster Daphnia_magna Carcinus_maenas Mammalia Homo_sapiens Mus_musculus Rattus_norvegicus 19 This will define the three tetraconata Drosophila melanogaste Daphnia magna Carcinus maenas as one monophylum and the three mammalia Homo sapiens Mus mus culus Rattus norvegicus as another one OGs will be selected for which at least one out of the three species is present Strategy 2 Selection of those OGs according to the existence in at least one sequence for each selected species You can simply copy the file containing all taxa in the study taxa_list txt and remove all unwanted Th
13. 1998 Phylogenomics Improving functional predictions for uncharacterized genes by evolutionary analysis Genome Res 8 3 163 167 Fitch W M 1970 Distinguishing homologous from analogous proteins Syst Zool 19 2 99 113 Gee H 2003 Evolution ending incongruence Nature 425 798 804 Koonin E V 2005 Orthologs paralogs and evolutionary genomics Annual Review of Genetics 39 309 338 Li L Stoeckert Christian J J and Roos D S 2003 OrthoMCL Identification of ortholog groups for eukaryotic genomes Genome Res 13 9 2178 2189 Mushegian A R Garey J R Martin J and Liu L X 1998 Large scale taxonomic profiling of eukaryotic model organisms a comparison of orthologous proteins encoded by the human fly nematode and yeast genomes Genome Res 8 6 590 598 O Brien K P Remm M and Sonnhammer E L L 2005 Inparanoid a comprehensive database of eukaryotic orthologs Nucl Acids Res 33 Database Issue D476 480 39 Tatusov R Fedorova N Jackson J Jacobs A Kiryutin B Koonin E Krylov D Mazumder R Mekhedov S Nikolskaya A Rao B S Smirnov S Sverdlov A Vasudevan S Wolf Y Yin J and Natale D 2003 The COG database an updated version includes eukaryotes BMC Bioinformatics 4 41 Wiens J 2006 Missing data and the design of phylogenetic analyses Journal of Biomedical Informatics 39 34 42 Zhang Z Schwar
14. 3 3497 3500 Delsuc F Brinkmann H and Philippe H 2005 Phylogenomics and the reconstruction of the tree of life Nature Reviews Genetics 6 5 361 375 Delsuc F Brinkmann H Chourrout D and Philippe H 2006 Tunicates and not cephalo chordates are the closest living relatives of vertebrates Nature 439 7079 965 968 Dessimoz C Boeckmann B Roth A C J and Gonnet G H 2006 Detecting non orthology in the COGs database and other approaches grouping orthologs using genome specific best hits Nucl Acids Res 34 11 3309 3316 Dolinski K and Botstein D 2007 Orthology and functional conservation in eukaryotes Annual Review of Genetics 41 465 507 Dress A Flamm C Fritzsch G Grunewald S Kruspe M Prohaska S and Stadler P 2008 Noisy Identification of problematic columns in multiple sequence alignments Algorithms for Molecular Biology 3 7 Dunn C W Hejnol A Matus D Q Pang K Browne W E Smith S A Seaver E Rouse G W Obst M and Edgecombe G D 2008 Broad phylogenomic sampling improves resolution of the animal tree of life Nature 452 7188 745 749 Duret L Mouchiroud D and Gouy M 1994 HOVERGEN a database of homologous vertebrate genes Nucl Acids Res 22 12 2360 2365 Edgar R C 2004 MUSCLE multiple sequence alignment with high accuracy and high through put Nucl Acids Res 32 5 1792 1797 Eisen J A
15. AAHHHAAAHE HAA HAAR AHA aH HEHHHHEHHHHAAHHHAA HHA AHA HEHHHHEHHHHEAHHHAA HH HEA AREA HE HH H ELIMINATING REDUNDANCIES HHEHHHHAAHHHAAHE HERA HHA AHA A Raa INPUT FOLDER FOR CALCULATION Name of directory in project directory distance_calculation_input basis_hits OUTPUT FOLDER FOR CALCULATION Name of directory in project directory distance_calculation_output reduced_genes ALIGNMENT METHOD 36 Options Muscle m T COFFEE t HHEHHHHAAHHHEAAH HAA HHA HAAR aH alignment_method m HEHHHHEHHHHEAHHHAA AHA RAE OTHER ALIGNMENT METHODS System call of different alignment method Use fasta_file_reduced as Input and final_alignment_file as Output e g for program xyz xyz in fasta_file_reduced out final_alignment_file HEEHHHHHHHHEHHHEEHHEHEHHHARRRE RHEE AS different_alignment_method HHEHHHHHHHHHEHHHHHHHAEHHAAEHHAHHERHE AH DISTANCE MATRIX TYPE Options From Alignment matrix type 1 a Custom Distance Matrix matrix type 2 g HEFHHHHHHHHEHHHEEHEAHEHHHERHRERRRH ARS distance_matrix_type g HHEFHHHHHHHHEHHHEEHEAHEHHHHRHRE RHEE ARS HHEFHHHHHHHHEHHHAEHEAHEHHHARREE HEARS HEHHHHHHHHEEHHHAA HH HRE AREA AE HHHHH POST PROCESSING HHHHHHHHHHH HEHHHHEHHHHEAHHHAA HHA AREA Select Method to be used Gblocks g Noisy n HHEHHHHAAHHHAAAHHRAAH HHA HARA Raa post_method g INPUT FOLDER Name of directory in project d
16. EST Format gt 3666157 1 will be converted to gt 3666157_1 Taxon_name 32 C 4 JGI transcripts Option s t JGI Transcript Format gt jgi Triad1 53994 fgeneshTA2_pg C_scaffold_3000001 will be converted to gt 53994 Taxon_name D Fasta Conversions Batch mode Example file for converting fasta headers in the correct format The syntax is FOLDER NAME_OF_SEQUENCE_FILE TAXON_NAME DATABASE_SOURCE An example file could be downloaded_sequences Oxytricha_trifallax_clusters Oxytricha_trifallax d downloaded_sequences Taphrina_deformans_clusters Taphrina_deformans d downloaded_sequences Triad1_best_transcripts fasta Trioplax_adhaerens t E Overview One letter functional classification used in the KOG database INFORMATION STORAGE AND PROCESSING J Translation ribosomal structure and biogenesis A RNA processing and modification K Transcription L Replication recombination and repair B Chromatin structure and dynamics CELLULAR PROCESSES AND SIGNALING D Cell cycle control cell division chromosome partitioning Y Nuclear structure V Defense mechanisms T Signal transduction mechanisms M Cell wall membrane envelope biogenesis N Cell motility Z Cytoskeleton wW Extracellular structures U Intracellular trafficking secretion and vesicular transport 0 Posttranslational modification protein turnover chaperones METABOLISM C Energy production and conversion G Carbohy
17. H RHEE HH HHHHHHH ORTHOLOGY SEARCH HHHHH HHEEHHHHHHHEEHHAEEHEEHHHHAEHRE HEHE RS Taxa List to analyse HHHHHHH Name of file in root directory taxa_list taxa_list txt HHH BLAST Options HHHHHHHHHH e_value 1e 10 HEHHHHHRHHAHHARHAEHAA RAHA THREAT Minimum length of Hit AA minimum_length_of_hit 10 HEHHHHHRHHAHHAEHAEHAAHRA HATHA ERR AE FOR PARTITIONED ANALYSIS 35 no_threads 2000 HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHEE HH HHHHHEHHHHHHHEHHAHHHEH HEHEHE HEHEHE HHHHH Statistics HHHHHHHHHHHHHHHHEHH HHHHEHHEHHHHEHHAHEHHH HEHEHE AHHH RH HHHHHHHHHHHHHHHHEH HEHEHE HERRERA HEHEHE LOCATION OF FOLDER CONTAINING TAXA OF INTEREST Name of file in project directory statistic_directory basis_hits LOCATION OF ANNOTATION FILE Name of file in root directory annotation_file db kog_list HHHHEHHHHHHHEHHAHEHHHHEHHEHRH AHHH HEH HHHHEHHHHHHHEHHAHHHEH HEHEHE AHHH HEH HHEHHHHAAHHHAAHHHRAAH HAA AHH AHA a SH GENE SELECTION OPTIONAL HHEHHHHAAHHHAAHH HAA HAAR AHA aH Options Single Taxa s Monophylum m HEHHHHEHHHHAAHHHAA HHA AHA gene_selection_option m LOCATION OF FOLDER CONTAINING TAXA OF INTEREST Name of directory in project directory gene_selection_directory selected_genes LOCATION OF FILE CONTAINING TAXA OF INTEREST Name of file in root directory required_taxa_file required_taxa_list txt HHEHHHH
18. OrthoSelect User Guide Fabian Schreiber March 18 2010 Disclaimer The program OrthoSelect is a beta test version which is still un der development The author is not aware of bugs that would cause the program to obtain incorrect results but they could exist Even though the author tries to make this program as reliable as possible it could be that parts of the program do not work as intended Please report any crashes bugs or problems you have with this program fschrei gwdg de This program is distributed in the hope that it will be useful but without any warranty License This program is copyright protected Results obtained with this pro gram can be published without restrictions provided the program and its au thors are acknowledged by name Future versions of this program are intended to be released under the Gnu Public License GPL Since the current version is a pre release version distributed merely by request from the authors it is not shipped with source code or the GPL Contents 1 Introduction 3 Script Overview N A How to use this manual or 6 Long Version Preliminary Work 6 3 1 Start the automated download 6 6 Orthologous Databases 6 7 Final Checks su su ee eog g ee ae a 7 The Main Analysis 7 1 Orthology Assignment ooa TZ StS 08 a apes a a Ae a E 7 3 Gene Selection Optional 7 4 Eliminating Redundancies
19. al method of ortholog prediction by including information from an ortholog database Other important aspects in data set construction for phylogenetic analysis on a large scale are 1 correct identification of open reading frames in ESTs and their translation 2 careful selection of target genes to maximize the phy logenetic information 3 elimination of redundant sequences and 4 a final refinement step to select conserved blocks and remove homoplasy from multiple sequence alignments Nowadays data sets in phylogenomic studies can easily contain dozens of taxa and hundreds of genes 2008 The construction of data sets of that size for phylogenomic studies is time consuming and can hardly be done manually 2 Program Overview The main workflow of the software pipeline to detect ortholog sequences in phylogenomic studies Input are EST libraries and an ortholog database either KOG or OrthoMCL DB as multi fasta files The analysis comprises four parts 1 The orthology detection which can be performed on a single computer or a computer cluster using a batch system e g Sun Grid Engine blasts each EST against the ortholog database selects the closest ortholog group as the best hit and translates it and stored together with the nucleotide sequences in the corresponding OG 2 Target genes can be selected 3 The sequence most likely being an ortholog is selected by eliminating potential paralogs 4 Alignments are refined to incre
20. ase phylogenetic signal Analysis Single Parallel Sequences Mul Multi Multi Multi FASTA FASTA FASTA FASTA 4 tvttitttit ORTHOLOGY SEARCH 4 E oso formatdb as AN gee 7 KA A a ea Select closest OG as best Hit _ gt A KA Translate EsTScan ae BioPer C IY Z Annotation h i 4 i t i i i i i 7 Lo Orthologous Database KOG or ORTHOMCL as fasta file Protein Sequences Nucleotide lt lt lt lt Cluster OGs Sequences gt Roses Ke Goa t ___ _ al SE tee m Elimination of redundant sequences C gt Alignment reduced S Alignment Refinement H Detect homoplastic characters Selection of conserved Blocks Noisy Gblocks Final Alignment 3 Script Overview This Figure shows the workflow of the software pipeline This time the name of the perl script in red as well as the name of the file s to be adapted in green are mentioned for each step of the analysis in gray The first step auto_ download pl is optional and will automatically download and install all required programs 0 00 _ Prepare Analysis EST databases in FASTA format req programs installed download ortholog database write file containing taxa in study Orthology Assignment Configuration fil
21. by the user needs to be within quotes E g project_name Example would be correct but project_name Example not The paths for files or folder need to end with an E g fasta_directory user home pipeline fasta_files would be correct but fasta_directory user home pipeline fasta_files not 6 6 Orthologous Databases Multi species ortholog databases have been developed on the basis of whole genome comparisons synteny and phylogenetic trees to include ortholog infor mation Two of these databases explicitly define ortholog groups OrthoMCL DB and NCBIs KOG which can be used as a basis for orthology assignment of unknown sequences using similarity searches To select an ortholog database simply edit the following line in the config uration file to choose KOG as the ortholog database orthology_database_type k To select the OrthoMCL DB enter o The download and configuration of the ortholog database will be done au tomatically see Section 6 7 12L ines starting with a hash key are comments 13 6 7 Final Check So far a lot of preliminary work has been done to prepare OrthoSelect on the system The following script will perfom the following tasks to make sure everything is set up for the main analysis see Section 7 to start e Check if the EST multi fasta files are in correct fasta format Check if all required programs are accessible and correctly installed Download the
22. drate transport and metabolism E Amino acid transport and metabolism F Nucleotide transport and metabolism H Coenzyme transport and metabolism I Lipid transport and metabolism 33 P Inorganic ion transport and metabolism Q Secondary metabolites biosynthesis transport and catabolism POORLY CHARACTERIZED R General function prediction only S Function unknown 34 F Format options_ txt HHEFHHHHHHHEEHHHEHHHAEHEHAEEHHEHHHEA HHA HHE HEHEHE HRHRHHREH RHE HHAEHRRRH HH Script name options txt Date created August 2008 Author Fabian Schreiber lt fschrei gwdg de gt This is the configuration file for OrthoSelect See the User manual for detailed descriptions HHH HH HOH H HF NOTE Paths must end with HHHHHEHEHHHHHHHHHHHHHHHHHHHHHHHEEHHHHHHEEEHHHHHEEHHHHHHHHHHHRHHHEEEH HEHEHE HHEHHHHHHHHEEHHHHHHHAEHHAEEHHAAHREE HE HHHHHHH PROJECT OPTIONS HHHHHHHH HHEEHHHHHHHEEHHAEEHEEHEHHHHRHRE HEH A RS PROJECT NAME project_name TEST ROOT DIRECTORY FOR ANALYSIS absolute pathname required root_directory Users home OrthoSelect HHEHHHHHHHHHEHHHHHHHAEHHAHEHHEHHEREE HH HHETHHHHHHHHEHHHHHHHAEHHAAEHHAHHHHE HE HHHHHHHERHHHHHHHHHHHAAH HAAR HH HHHHHHH ORTHOLOG DATABASE HHHHHHHHH HHHHHHHHHHAREHHHHHHHERR RARER HH Database to blast against KOG k OrthoMCL o HHHHHHHHHHARHHHHHHHHRRR RARER HH orthology_database_type k HHHHHHHAEHHHHHHHHHHHAAHAA ARH HHEHHHHHHHHHEHHHHHHHHEHHAAEHHA
23. e profile 8 1 2 Fasta files Our test data set consists of EST sequences and transcripts shown in the table below downloaded from J GP Taxon File name Type of sequence Aspergillus niger Aspnil_Filtered Models1 na fasta Transcripts Ciona intestinalis Cintestinals_ EST _clusters fasta ESTs Daphnia pulex FrozenGeneCatalog_2007_07_03 na fasta Transcripts Lottia gigantea Lotgil_EstClusters_na fasta ESTs Monosiga brevicollis Monbr1_ESTclusters fasta ESTs The files are in the folder test data Currently the fasta headers of these files look like this File test_data Aspni1_FilteredModels1 na fasta Header gt jgi Aspni 202811 estExt_fgenesh1_pg C_20516 File test_data Cintestinals_EST_clusters fasta Header gt 847937 2 File test_data FrozenGeneCatalog_2007_07_03 na fasta Header gt jgilDappul 48454 gw1 58 76 1 File test_data Lotgi1_EstClusters_naClusterCr705LottiaJgi20060727 fasta Header gt 4243977 1 File test_data Monbri_ESTclusters fasta Header gt 3716647 1 19see section for details about other operating systems 20 The full filename of Lottia gigantea is Lotgil_EstClusters_naClusterCr705LottiaJgi20060727 fasta but has been reduced to save space 25 Since a correct fasta header is a precondition for a successful analysis we make sure that the fasta headers are all in correct format To automatically rename the fasta headers we write the following information in a file called
24. e options txt single CPU start_orthology_assignment_single pl Cluster SGE start_orthology_assignment_cluster pl Gene Selection onfiguration file options txt gene_selection pl single CPU start_filter_redundant_single pl Cluster SGE start_filter_redundant_cluster p L C Final Alignment Analysis 4 Data Overview This Figure shows an overview of the directory structure that is created by the software pipeline throughout the analysis The root directory is the di rectory where the software pipeline is installed The lib directory contains required Perl modules the db will contain the automatically downloaded or tholog database and additional files The EST libraries in fasta format will be stored in a directory in this case test data and the test data directory con tains the EST libraries in fasta format All results will be stored in the project directory Results from the orthology assignment will be stored in basis hits and annotations in annotation Further results such as the selected target genes in this case selected genes the genes where redundant sequences have been eliminated and the post processed in this case reduced genes will be stored in different folders 5 Homo Mus annotation Sapiens Musculus Dod Ddd b Homo sapiens Mus Musculus asis i hits DOJ Rattus norvegicus project directory selected hit
25. e file could look than as follows Aspergillus_niger Aspergi_ni Ciona_intestinalis Ciona_in Lottia_gigantea Lottia_gi Perform Analysis Start the analysis by typing perl perl_scripts gene_selection pl Output By default the results will be stored in the subfolder selected_hits of the project folder 20 7 4 Eliminating Redundancies Multiple divergent copies of the same gene and different levels of stringency during EST assembly can lead to the situation where OGs contain more than one sequence per species The same is true for the ortholog groups contained in KOG where many groups contain both orthologs and paralogs 2006 In these cases a fast and reliable method is needed to select the best sequence per species Assuming that orthologs between organisms are more similar to each other than to paralogs all sequences belonging to the same OG are aligned and two types of distance matrices can be used to decide which sequence is to be kept for further analysis These two matrix types are 1 An initial distance matrix as computed by alignment methods like Clustal W Chenna et al 2003 2 A specialised distance matrix selecting those sequences that have the high est number of matching positions in pairwise comparisons using Muscle Eder 2008 Options Set the following options in the configuration file options txt by default distance_calculation_input selected_genes distance_calculation_outpu
26. irectory post_process_directory reduced_genes HHHHH GBLOCKS H HHHHHHHHHHHHH PARAMETERS FOR GBLOCKS leave blank for defaults gblocks_b1i gblocks_b2 gblocks_b3 gblocks_b4 gblocks_b5 ue HHEHHHHAAHHHEAAH HHA HHA AHA A HAA Filter sequencing with less than X character post_alignment_filter t post_alignment_threshold 50 HHEHHHHEHHHHEAHHHEA HHA AERA RAH 37 38 References Altschul S Madden T Schaffer A Zhang J Zhang Z Miller W and Lipman D 1997 Gapped BLAST and PSI BLAST a new generation of protein database search programs Nucl Acids Res 25 17 3389 3402 Bourlat S J Juliusdottir T Lowe C J Freeman R Aronowicz J Kirschner M Lander E S Thorndyke M Nakano H and Kohn A B 2006 Deuterostome phylogeny reveals monophyletic chordates and the new phylum xenoturbellida Nature 444 7115 85 88 Castresana J 2000 Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis Mol Biol Evol 17 4 540 552 Chen F Mackey A J Stoeckert Christian J J and Roos D S 2006 OrthoMCL DB query ing a comprehensive multi species collection of ortholog groups Nucl Acids Res 34 Database Issue D363 368 Chenna R Sugawara H Koike T Lopez R Gibson T J Higgins D G and Thompson J D 2003 Multiple sequence alignment with the Clustal series of programs Nucl Acids Res 31 1
27. lastall Either you havent installed blastall or you are using a different shell and this shell does not know where to find blastall Either type source HOME profie where HOME is your home directory to re read the profile file or perl auto_download pl to install the missing blastall package Problem Can t locate LWP Simple pm in INC Solution Your system cannot find the Perl module Simple pm from the pack age LWP Install it by typing perl MCPAN e install LWP Simple 31 A Format required_taxa_list txt Selection strategy based on defined monophyla MonophylumX Species_name Species_name Monophylumi Monosiga_ovata Monosiga_brevicollis Monophylum2 Homo_sapiens Mus_musculus B Format taxa_list txt Species_name Species_name_shortcut e g Acropora_millepora Acropor_mi Allomyces_macrogynus Allomyc_ma Amphimedon_queenslandica Amphime_qu C Fasta Conversions Possible conversions of fasta headers using the script fasta header converter pl C 1 dbEST Option s n dbEST Format gt gil 166077299 gb FD528199 1 FD528199 RUS94C02w HZ Hordeum vulgare subsp will be converted to gt 166077299 Taxon_name C 2 TBestDB Option s d TBestDB Format vulgare cDNA clon gt Cluster Id ACL00003079 AutoFACT Annotation 14 3 3 like regulatory protein will be converted to gt ACL00003079 Taxon_name C 3 JGI ESTs Option s e JGI
28. ll be in the directory perl scripts and need to be entered as mentioned in the example http www finkproject org http www macports org 11 or gt 1d203335 SOME_ANNOTATION would be a correct format This format will be important when the program needs to distinguish between sequences from the same species see Section 6 4 2 The script in Section P will try to do this in an automatic way for yo Name of fasta files Fasta files should be named according to the taxon they belong to E g ESTs from Aspergillus niger should be saved in a file Aspergillus_niger fa Naming of files is important since OrthoSelect will automatically generate a file containing all taxa in the study See Section 6 7 Fasta files can automatically adapted using the following script Fasta Script The following script works for sequence data downloaded from either the JGI websitd or TBestDE Assuming that a fasta file containing transcripts is downloaded from JGI and is stored in the appropriate directory that is est_libraries type the following to change the fasta headers of the file ests_from_aspergillus_niger fa and name the file Aspergillus_niger fa perl perl_scripts fasta_header_converter pl i est_libraries ests_from_apergillus_niger fa t Aspergillus_niger s t For sequences downloaded from TBestDB please type s d for EST sequences downloaded from JGI please type s e and for sequences down
29. lly conserved whereas paralogs tend to have different functions and are less useful in phylogenetic studies A typical protocol for detecting orthologs in phylogenomic studies should include 1 a similarity search using tools like BLAST 1997 2 a strategy to select a subset of hits returned by this search 3 a criterion to identify sequences as potential orthologs 4 a strategy for eliminating potential paralogs in case several potential orthologs from the same species have been assigned to the same OG Orthology assignment is a crucial prerequisite for phylogeny reconstruction as faulty assumptions about orthology e g the inclusion of paralogs can lead to an incorrect tree hypothesis 2002 Errors can re sult from similarity searches against non specialized databases e g NCBI s nr database or from best hit selection strategies such as best reciprocal hit or best triangular hit that may lead to false positive orthology predictions The similarity between a query and a database sequence stemming from a similarity search expressed for example as a bit score or expectation value is usually taken as a criterion to predict an ortholog relationship Since the results of these methods depend on the choice of a database and on the strategy to select sequences from similarity search hits a more reliable protocol for ortholog predictions is needed Several databases and computational methods for predicting orthologs have been im
30. loaded from dbEST please type s wP Fasta Script batch mode Adapting the fasta header of several est libraries can also be done in batch mode For this simply enter the following information in a file and save it under taxa_conversion txt This file should include the name of the est libraries the name of the taxons and the source of the est libraries as described above For an example see Appendix D The conversion can then be started typing perl perl_scripts fasta_header_converter pl Alternatively to using the script you can use a stream editor such as sed or perl s one linerd 6Note that since the fasta header does not require a clear syntax there is no guarantee l0visit e g visit e g Appendix C http www student northpark edu pemente sed sediline txt http sial org howto perl one liner 12 6 5 The configuration file The configuration file contains all important parameters and settings This is the main file that has to be adapted by the user All perl scripts use the information contained in the configuration file to perform the BLAST searches calls of external programs input output actions etc By default the name of the configuration file is options txt See Appendix F for an example of a full configuration file The file consists of simple key value saint E g project_name Example This allows the user to set a project name Note that every value entered
31. matically select conserved blocks from multiple sequences for their use in phylogenetic analysis For more information about the programm see the user manual of Gblocks Options Set the following options in the configuration file options txt by default post_method g The post processing method g stands for the post processing of alignments using Gblocks n stands for post processing using Noisy post_process_directory reduced_genes This is the directory where the post processed files will be saved The Gblocks parameters can be adjusted by changing the following values in the configuration file HHHHH GBLOCKS HHHHHHHEH gblocks_bi gblocks_b2 gblocks_b3 gblocks_b4 gblocks_b5 22 By default Parameters left blank OrthoSelect uses Gblocks with standard setting Filter out sequences with a user defined percentage of missing char acters Based on the alignment processed using Gblocks the user can select to filter out sequences with a percentage of characters below a user defined threshold To activate this option the following parameter have to be set in the configuration file post_alignment_filter t post_alignment_threshold 50 where post_alignment_filter t turns the filter on default is post_alignment_filter t and the filtering option turned off and post_alignment_threshold 50 means that sequences with less
32. operly set A reason could be that a previous ESTScan installation has been deleted without deleting the corresponing environmental variable The variable has to point to the ESTScan directory containing the matrix file Hs smat by default Solution Type echo export ESTSCANDIR dir gt gt profile where dir is the installation directory of ESTScan By default this is a subdi rectory in the OrthoSelect directory Error Fatal Error Could not build objects Problem GENEWISE cannot find several matrices for translation The en vironmental variable WISECONFIGDIR is not properly set The variable has to point to the WISECONFIGDIR directory containing several matrix files e g blosum62 bla Solution Type echo export WISECONFIGDIR dir wisecfg gt gt profile where dir is the installation directory of WISECONFIGDIR By default this is a subdirectory in the OrthoSelect directory Error I used the perl script auto_download pl to download all required programs but they do not seem to be installed Problem It is possible that your shell does not know yet where to search for the installed programs This information has been added to your profile file during the execution of the perl script Your shell needs to re read the profile file Solution Type source HOME profie where HOME is your home directory 30 Problem MSG cannot find path to blastall Solution OrthoSelect cannot find b
33. ortholog database specified by the user Turn the ortholog database in a blastable database e Test the ortholog database by performing a test BLAST search Write a file containing all taxa in the study taxa_list txt Options You need to tell the script the location where you installed OrthoS elect You can also give your analysis a project name To do this set the following options in the configuration file options txt by default project_name Example root_directory user home OrthoSelect The root_directory is the directory where OrthoSelect is installed The project folder will be created in the root_directory as can be seen in Figure All results and data will be saved in the project folder The ortholog database will be installed in the db directory see Fig Perform Analysis The script can be called as follows perl perl_scripts prepare_analysis pl Taxa file An overview of the taxa present in the study will be written in the file taxa_list txt The file will also contain a recommended shortcut for each taxon name This is because some alignment viewer or formats e g the phylip format can restrict the length of taxa names to 10 characters The shortcuts will be later used in the fasta headers Make sure that each shortcut is a unique identifier of a taxon E g If you have the two blood flukes Schistosoma mansoni and Schistosoma malayensis present in your study The recommended shortcu
34. plemented Multi species ortholog databases have been developed based on different sources of ortholog information They include information about ortholog relationships between sequences The OrthoMCL DB database has been constructed on the basis of whole genome comparisons HomoloGene Zhang et al 2000 on the basis of synteny and HOVERGEN Duret et al 1994 was constructed using the information from phylogenetic trees Two of these databases OrthoMCL DB and KOG Tatusov et al 2003 explicitly define ortholog groups OG which can be used as a basis for orthology assignment of unknown sequences using similarity searches Ortholog groups in these databases have been identified by analyzing complete genomes Most computational methods to identify orthologs are based either on a phy logenetic analysis or on all against all BLAST searches 2007 The former approach is computationally expensive and usually requires manual intervention All against all approaches use every sequence from the input data set as a query for BLAST searches against the sequences from the respective other species This approach generates OGs based on some similarity measure e g using all best reciprocal hits These OGs can be further processed to merge delete or seperate overlapping groups using a clustering algorithm as has been done e g for OrthoMCL Li et al 2003 or Inparanoid O Brien et al 2005 Zhou and Landweber 2007 implemented a computation
35. pplied The ortholog database will be converted in a BLAST database as well as clustered in ortholog groups Each EST sequences upper left from the EST library is assigned to that OG lower left returned by a BLASTO search against the ortholog database upper right Options Set the following options in the configuration file options txt by default taxa_list taxa_list txt e_value te 10 minimal_length_of_hit 10 no_threads 2000 Simply enter the name of the file containing the taxa whose EST libraries you want to analysq 4 by default all taxa will be analysed and the expectation value E value no_threads is only available with an analysis using a computer cluster It will do the following E g if a EST library contains 40 000 sequences the analysis will be split into 4 parts of 10 000 no_threads sequences each and will be parallel analysed to increase the speed of the orthology search All hits with less than 10 AA positions will be discarded Perform Analysis Two options are available For the analysis on a single computer e g Desktop type perl perl_scripts start_orthology_assignment_single pl For the analysis on a computer cluster with a sun grid engine type perl perl_scripts start_orthology_assignment_cluster pl The file taxa_list txt will be automatically created in Section 6 7 16 Output By default the results will be stored in the subfolder basis_hits of the
36. roteins the next step is the proper selection of OGs suitable for phylogenetic analysis Since EST libraries represent snapshots of expressed genes not every OG will contain EST sequences from all species under study some OGs may contain only a few sequences Such OGs do not contain sufficient information and are therefore not suitable for further consideration On the other hand we do not require every OG to contain all sequences of interest So far there is no consensus about the influence of missing genes on the resulting phylogeny exists 2006 so there is no reliable criterion which OGs should be used for phylogenetic inference Our software offers the following three options 1 The user selects a group of species In this case those OGs will be selected that contain ESTs from all of the user selected species 2 The user defines groups of species Our tool will then select those OGs that contain at least one EST sequence for each of the specified groups 3 The selection of OGs based on a user defined percentage of missing data The selection of genes according to the existence of user selected taxa can be useful to reduce the number of OGs to a manageable set of OGs In order to skip the step of the analysis one can simply set go to Section 7 4 and enter basis_hits as the distance_calculation_input Remember that basis_hits is the directory containing all OGs after the orthology search see Sec 7 Options Set
37. s reduced OG o hits 2 perl Perl re Script scripts ener Perl Modules Ortho Select some directory Ortholog Database est_ i EST libraries libraries 5 How to use this manual The main purpose of this manual is to make the user familiar with OrthoSelect and provide the user with every information to use OrthoSelect For this we splitted this manual into two parts The first part in section 6 is a long version of how to use OrthoSelect It includes detailed information for each step of the analysis Taxon names used in that section are used as examples only They should be replaced by the real taxa names in the study Contrary to that section 8 is a short and quick guide to start the analysis This part can also be regarded as a tutorial 6 Long Version Preliminary Work Contrary to the previous section this section gives a more theoretical and de tailed overview of all available options and parameters of OrthoSelect Taxa names in this section are used as examples only They should be replaced by the real taxa names in the study 6 1 Preliminary steps The section describes some preliminary steps to prepare your system and the data for the analysis It covers the download and installation of external pro grams as well as the selection of an ortholog database and a final check if ev erything is correctly set up
38. sure that the configuration file has the following entries post_method g post_process_directory reduced_genes post_alignment_filter t post_alignment_threshold 50 We start the analysis by typing perl perl_scripts post_processing pl The blocked alignments as well as the filtered alignments will be put in the same folder So the folder containing the OG KOG0213 will contain the following files K0GO213_final fasta K0GO213_final_gblocked fasta K0GO213_final_gblocked_filtered fasta K0GO213_nucl_hits fasta K0GO213_prot_hits fasta LOG_rejected_sequences txt You can now view the blocked alignment KOG0213_final_gblocked fasta and compare it to the filtered alignment KOG0213_final_gblocked_filtered fasta to see how the filter option works Conclusion This was a short example to show how easy OrthoSelect can be used Since paralogs can be selected in case orthologs are missing either in the study or in the species all temporary results and especially the final alignments should be checked with much care At this point the user should be more or less familiar with the way OrthoSelect works The user can now read the next chapter to perform the analysis using real data 29 9 Troubleshooting 9 1 Error Messages Error No CDS matrix found for 29 6666666666667 GC at sw estscan BTLib 2 0b ESTScan ESTScan line 160 line 6 Problem ESTScan cannot find a CDS matrix The environmental variable ESTSCANDIR is not pr
39. t reduced_genes for the input and output directories for this step of the analysis alignment_method m Selection of the alignment method used to align the sequences in an ortholog group Use m to align the sequences using Muscle and t to align the se quences using T coffee distance_matrix_type g For matrix type 1 select a and for matrix type 2 select g Other Alignment Methods The user can use any alignment method avail able by providing the command line call of the alignment method E g if the user wants to use the alignment method align then he needs to provide the system call of the program align and replace the input and output file name by fasta_file reduced and final_alignment_file respectively The appropriate value in the configuration file should look then as follows different_alignment_method align in fasta_file_reduced out final_alignment_file Perform Analysis Again two options are available For the analysis on a single computer e g Desktop type perl perl_scripts start_filter_redundant_single pl For the analysis on a computer cluster with a sun grid engine type perl perl_scripts start_filter_redundant_cluster pl 16Note that this step can take a while depending on the size of the OGs 21 Output By default the results will be stored in the subfolder reduced_genes of the project folder The alignments will have the postfix final fasta un
40. tance matrix that is used to select the sequences most likely to be an ortholog is calculated from the alignment The sequence will be aligned using muscle So make sure that the configuration file has the following entries distance_calculation_input selected_genes distance_calculation_output reduced_genes alignment_method m distance_matrix_type g We start the analysis by typing perl perl_scripts start_filter_redundant_single pl After the analysis has finished the ortholog group e g KOG0213 will then contain the following files K0GO0213_final fasta K0GO213_nucl_hits fasta K0GO0213_prot_hits fasta with the unaligned protein and nucleotid sequences in KOG0213_prot_hits fasta and KOG0213_nucl_hits fasta respectively The alignment containing only the best sequence for each taxon is KOG0213 _final fasta 28 8 6 Alignment Curation The final step is the automatic curation of alignments with the goal to select potential conserved region or remove homoplastic sites In this case we want to select potential conserved regions of our alignments using Gblocks We will use Gblocks with default settings here and our alignments are in folder reduced_genes We also want to get rid of too short sequences Therefore we turn the post_alignment_filter on in the configuration file and set the threshold to 50 to allow only sequences that have at least half the length of all other sequences We make
41. than 50 of characters in the alignment are dis carded Perform Analysis Start the analysis by typing perl perl_scripts post_processing pl 7 5 2 Noisy Noisy is a program that tries to eliminate potentially homoplastic sites in multiple sequence alignments For more information about the programm see Dress et al 2008 Options Set the following options in the configuration file options txt by default post_method n The post processing method g stands for the post processing of alignments using Gblocks n stands for post processing using Noisy post_process_directory reduced_genes This is the directory where the post processed files will be saved Perform Analysis Start the analysis by typing perl perl_scripts post_processing pl 7 5 3 AliScore Aliscore is a program that identifies regions in the alignment that show random sequence similarity 17 for a detailed description see molevol ibmb csic es Gblocks html 18Due to difficulties installing this software we do not offer to automatically install these software Nevertheless Noisy can be used by OrthoSelect if it is manually installed 23 Options Set the following options in the configuration file options txt by default aliscore y post_process_directory reduced_genes This is the directory where the post processed files will be saved Perform Analysis Start the analysis by typing perl perl_scripts
42. ts will be Schistosoma_mansoni Schisto_ma Schistosoma_malayensis Schisto_ma Since the program will only deal with the shortcut form you have to change the appropriate entry to e g Schistosoma_mansoni Schisto_ma Schistosoma_malayensis Schisto_my 13Note that it can take some time to download the ortholog databases depending on the connection speed and the size of the database KOG 50 Mb OrthoMCL DB DB 400 Mb 14 to avoid the program treating both taxa as the same On the other hand if you have several data source for one taxon e g transcripts and est sequences then choosing the same shortcut for each data source will let the program select the best sequence from all data sources Note If you want to analyze protein sequence rather than EST sequences you simply have to add a p after each taxon Edit the taxa file as follows Schistosoma_mansoni Schisto_ma p Schistosoma_malayensis Schisto_my p With this the program assignes protein sequences to OGs using blastp instead of blastx as with EST sequences 15 7 The Main Analysis 7 1 Orthology Assignment The first step of the software pipeline comprises the detection of potential or thologs in EST libraries see Figure 1 ae T pe Ortholog Database Single EST Clustered Ortholog Groups Figure 1 Workflow of orthology detection in detail The two databases colored in green are user su
43. tz S Wagner L and Miller W 2000 A greedy algorithm for aligning DNA sequences Journal of Computational Biology 7 1 2 203 214 Zhou Y and Landweber L F 2007 BLASTO a tool for searching orthologous groups Nucl Acids Res 35 Web Server Issue W678 682 Zmasek C and Eddy S 2002 RIO Analyzing proteomes by automated phylogenomics using resampled inference of orthologs BMC Bioinformatics 3 14 40
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