Java tutorial: Programmatic Access to Molecular Interactions
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Networks and Pathways Bioinformatics for Biologists. 12 July 2013
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Java tutorial: Programmatic Access to Molecular Interactions
- 1. v.1.0 - 10/07/2013 Programmatic Access to Molecular Interactions Bruno Aranda (baranda@ebi.ac.uk) Samuel Kerrien (skerrien@ebi.ac.uk) Rafael C Jimenez (rafael@ebi.ac.uk) Contents
- 4. Course Information Course description This course is an introduction to programmatic access to Molecular Interactions. It covers Standard Formats and Protocol enabling access to Molecular interactions as well as libraries to facilitate their usage. Course level This course is primarily aimed at beginners/intermediate in the field of Molecular Interactions with programmatic knowledge in Java and Web Services. Prerequisites Participants are expected to have solid knowledge of Java and Web Services technology. Subject area Molecular Interactions, Data Standards. Target audience Postdocs, PhD, students in Bioinformatics or Computer Science. Resources required Internet access (browser: Firefox or Chrome), Linux or Windows (with POSIX commands available, e.g. Cygwin) Java 7 (JDK, not JRE) Maven 3 Java IDE such as IntelliJ or Eclipse Cytoscape 2.7 or above Approximate time needed 3 hours Course learning objectives ● Learn what the IntAct project is providing your with and try out the web site; ● Learn about standardisation effort in the field of molecular interactions; ● Gain a practical experience of handling the various standards available; ● Discover how PSICQUIC give you easy access to vast amount of data.
- 5. Introduction to Molecular Interactions Studying molecular interactions provides valuable insights into understanding a molecule's role inside a specific cell type. There are several families of experimental protocols commonly used to identify molecular interactions: ● Complementation assays (e.g. 2hybrid) measure the oligomerizationassisted complementation of two fragments of a single protein which when united result in a simple biological readout – the two protein fragments are fused to the potential bait/prey interacting partners respectively. This methodology is easily scalable to high throughput since it can yield very high numbers of coding sequences assayed in a relatively simple experiment and a wide variety of interactions can be detected and characterized following one single commonly used protocol. However, the proteins are being expressed in an alien cell system with a loss of temporal and physiological control of expression patterns, resulting in a large number of false positive interactions being observed. ● Affinitybased assays (e.g. affinity chromatography, pulldown and coimmunopreciptiation), rely on the strength of the interaction between two entities. These techniques can be used on interactions which form under physiological conditions but are only as good as the reagents and techniques used to identify the participating proteins. ● Physical methods (e.g. Xray crystallography and enzymatic assays) depend on the properties of molecules to enable measurement of an interaction. High quality data can be produced but highly purified proteins are required, which has always proved a rate limiting step. Availability of automated chromatography systems and custom robotic systems that streamline the whole process, from cell harvesting and lysis through to sample clarification and chromatography has changed this and increasing amounts of data are being generated by such experiments. Molecular interactions are crucial components of the cellular process. In order to understand this complex machinery, one needs to gather published data from various sources. Many projects have initiated the collection of interaction data for this purpose since 2002. However, the lack of standardisation previously made the task of aggregating datasets difficult. This issue has been resolved by the creation of Molecular Interaction standard in 2004 by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO). Furthermore, major database providers have come together with the goal to exchange data in order to optimise laborious curation tasks. Finally, tools and frameworks have been created based on PSIMI standards to facilitate the visualisation and analysis of molecular interaction data. Molecular interactions are generally represented in graphical networks with nodes corresponding to the molecules and edges to the interactions. Although edges can vary in length most networks represent undirected and only binary interactions. Bioinformatics tools and computational biology efforts into graph theory methods have and continue to be part of
- 6. the knowledge discovery process in this field. Analysis of interaction networks involves many challenges, due to the inherent complexity of these networks, high noise level characteristic of the data, and the presence of unusual topological phenomena. A variety of datamining and statistical techniques have been applied to effective analyze interaction data and the resulting networks. The major challenges for computational analysis of interaction networks remain: ● unreliability of large scale experiments; ● biological redundancy and multiplicity: a protein can have several different functions; or a protein may be included in one or more functional groups. In such instances overlapping clusters should be identified in the PPI networks, however since conventional clustering methods generally produce pairwise disjoint clusters, they may not be effective when applied to PPI networks; ● two proteins with different functions frequently interact with each other. Such frequent, connections between the proteins in different functional groups expand the topological complexity of the PPI networks, posing difficulties to the detection of unambiguous partitions. Intensive research trying to understand and characterize the structural behaviours of such systems from a topological perspective have shown that features such as smallworld properties (any two nodes can be connected via a short path of a few links), scalefree degree distributions ( powerlaw degree distribution indicating that a few hubs bind numerous small nodes), and hierarchical modularity (hierarchical organization of modules) suggests that a functional module in an interaction network represents a maximal set of functionally associated molecules. In other words, it is composed of those molecules that are mutually involved in a given biological process or function. In this model, the significance of a few hub nodes is emphasized, and these nodes are viewed as the determinants of survival during network perturbations and as the essential backbone of the hierarchical structure.
- 7. Tutorial Setup In the following part we will only use UNIX Bash Shell command line, please use their corresponding counter part if your use an other Shell interpreter or Operating System. Java Download: http://www.oracle.com/technetwork/java/javase/downloads/index.html Steps 1. Download and install Java in a directory of your choice (e.g. /lib/jdk7); 2. Set the following environment variable: JAVA_HOME and PATH as follow: a. export JAVA_HOME=/lib/jdk7 b. export PATH=${JAVA_HOME}/bin:${PATH} 3. Open a new shell and type java version to check your have the right version. Maven 3 Download: http://maven.apache.org/download.html Steps 1. Download and unpack Maven in a directory of your choice (e.g. /lib/maven3); 2. Set the following environment variable: M2_HOME and PATH as follow: a. export M2_HOME=/lib/maven3 b. export PATH=${M2_HOME}/bin:${PATH} 3. Open a new shell and type mvn version to check your have the right version. Alternatively, you can follow the installation instructions provided by Apache: http://maven.apache.org/download.html#Installation Subversion Download: http://subversion.apache.org/packages.html Steps 1. Download and unpack Subversion in a directory of your choice (e.g. /lib/svn); 2. Set the following environment variable: PATH as follow:
- 8. a. export PATH=/lib/svn/bin:${PATH} 3. Open a new shell and type svn version to check your have the right version. Java IDE There are several major Java IDE available online and we are only giving information about Eclipse and IntelliJ (that is our favorite in the IntAct team). Download Eclipse: http://www.eclipse.org/downloads Steps 1. Download and unpack Eclipse for Java Developer edition, then launch Eclipse; 2. Next step is to add support for Maven, to do so, open the Overview windows (figure 1) and click on the Eclipse Marketplace. Install the Maven integration plugin (figure 2); Alternatively, you can also click Help > Eclipse Market Place; 3. Restart Eclipse so that our newly installed plugin becomes available. Figure 1. Eclipse Overview Figure 2. Maven plugin Download IntelliJ: http://www.jetbrains.com/idea/download Steps 1. Download and unpack IntelliJ; 2. Launch IntelliJ. Note IntelliJ has inbuilt Maven support so no additional plugin need installing at this stage.
- 9. Information about this Tutorial Download the course source code In a shell, type the following command: svn co http://intact.googlecode.com/svn/repo/site/trunk/intactcourse This will create a directory called intactcourse in the directory where you ran the command. Prepare the project Now we will ensure that all required third party libraries required by Maven and the intactcourse are going to be downloaded locally. This ensures that that Maven works smoothly even if you don’t have an internet connection available. Get into the intactcourse directory and type: mvn clean dependency:gooffline This may take several minutes so please be patient. Open the project in your favorite Java IDE Eclipse Steps 1. Go to the intactcourse directory and type mvn eclipse:eclipse DdownloadSources 2. In Eclipse, open File > Import; 3. Choose as a project type: General > Existing project into Workspace (Fig. 1.); 4. Browse and select the intactcourse directory (Fig. 2.); Click Finish.
- 10. Figure 3. Choosing a project type Figure 4. Select your project location Eclipse asks for a password (for secure storage). Just cancel and ignore. IntelliJ Steps 1. Open File > Open project; 2. In the intactcourse directory select the file pom.xml to open the project. IntelliJ will open the project and use the maven configuration to setup your classpath automatically.
- 11. intactcourse project structure The intactcourse directory is structured as follow: ● pom.xml: Maven configuration for the project, including declaration of required third party libraries, plugins (e.g. Java compiler)... ● src/main/java: source code for the course including exercises and solutions; ● src/main/resources: configuration files and sample data files required to run some exercises. How to run an exercise class ? Each java based exercises provided is encoded in a dedicated class file for which the package reflect the context of the exercise. Example: intact.solution.psicquic.registry.ListingAllServices Each of these classes has a main method so running it is easily done as explain below: Command line with Maven Steps 1. Go into the intactcourse directory 2. get the reference of the class you want to run, for instance: intact.solution.psicquic.registry.ListingAllServices 3. Type: mvn exec:java Dexec.mainClass=intact.solution.psicquic.registry.ListingAllServices Eclipse Steps 4. Right click on the class you want to run and choose: Run As > Java Application 5. If not done already, the project will compile and the output of the class will be shown in a console. IntelliJ Steps 1. Right click on the class you want to run and choose: Run 2. If not done already, the project will compile and the output of the class will be shown in a console.
- 13. PSIMITAB Learning objectives ● What are the various version of the MITAB formats, their strengh and shortcomings; ● Learn how to find MITAB content from IntAct and other resources; ● Gain practical experience of parsing MITAB. Exercises Exercise 1: Programmatic Access using the command line Nofrills access to the data, using the IntAct REST example URL. Steps 1. Open the PSICQUIC Registry page in your web browser: http://bit.ly/psicquicregistry; 2. Each PSICQUIC service has an example link to demonstrate a sample REST query, copy the URL of a service in your clipboard as shows in Figure 2.1 below; 3. Open this URL in the address bar of a new window in your web browser: 4. http://cicblade.dep.usal.es/psicquicws/webservices/current/search/interactor/P0053 3; 5. Your should view MITAB data being downloaded from the APID PSICQUIC service. Figure 2.1. Copying the REST example URL from the APID PSICQUIC service. Question 1: Using the command line wget, download MITAB data from IntAct and store it in a file called intact.tsv Information
- 14. Should you not be familiar with wget, type man wgetin a terminal to get access to documentation. Typically, downloading the content of a URL into a file is done as follow: wget “<URL>” O output.txt Bear in mind that a URL can contain special characters (e.g. &) that can be conflicting with your command line, to avoid this happening, make sure to surround your URL with double quotes. Question 2: Using the grepcommand, count how many interactions involve the protein P03120. Information There are many ways to perform this task but here are a few command line tools that may help you: ○ cat <file>: prints on the standard output the content of the file given as parameter; ○ grep <value>: prints on the standard output all lines containing the value given as parameter; ○ wc l: prints a count of line of the data received on standard input. UNIX command lines can be chained together using the symbol |so that the output of the preceding command is given as input to the following one. For instance cat file.txt | wc l would print the count of line in file.txt Exercise 2: Using the Java library for MITAB In this section, your will benefit from using a Java IDE such as Eclipse or IntelliJ to facilitate the use of Maven, source code compilation, running the exercises... This java library takes care of parsing MITAB25 data, making each MITAB line parsed into a Java object: Question 1: Can you write a class that reads a MITAB data file/stream and print out the count of interactions parsed? intact.exercise.chapter2.exercise2.Q1_ReadWholeFile Question 2: Should you attempt to load the whole content of a data file/stream into memory could cause problems if the volume of data is large. To facilitate this the class psidev.psi.mi.tab.PsimiTabReaderalso allows developers to iterate over the data. Now write an other program (similar to question 2) that implements this more efficient memory management. intact.exercise.chapter2.exercise2.Q2_ClientAndMitabBetterMemory
- 15. Question 3: Now that we have read the content of a MITAB file/stream, we can attempt to write this content back to a file. Write a program that writes the MITAB content read into a file. intact.exercise.chapter2.exercise2.Q3_WriteToFile Exercise 3: Indexing MITAB data locally using Lucene Question 1: This library offers the possibility to to index a MITAB dataset using Lucene. This enables users to run local MIQL queries, thus easing data processing. Write a program that indexes the provided MITAB data file. intact.exercise.chapter2.exercise3.Q1_IndexMitabFile Information Apache Lucene is a highperformance, fullfeatured text search engine library written entirely in Java. It is a technology suitable for nearly any application that requires fulltext search. You can find more information about Lucene on the Apache web site. A reference to MIQL is provided below (Fig. 2.2.). Figure 2.2. MIQL fields reference. Question 2: Write a program that queries the local Lucene index to search for interaction evidences involving specific molecules. For instance by uniprot identifier O45406 or pubmed id 17129783. intact.exercise.chapter2.exercise3.Q2_QueryLocalIndexUsingMIQL
- 16. Question 3: Like MITAB2.6 and higher, the IntAct extended MITAB format does have a column that describe potential complex expansion that may have been applied to generate binary interactions. Write a program that reads an IntAct MITAB file and print the following: ● total count of interactions; ● count of spoke expanded interaction; ● count of experimentaly identified binary interaction (i.e. not expanded). intact.exercise.chapter2.exercise3.Q3_FilterSpokeInteractions
- 17. PSICQUIC Learning objectives In this introductory chapter about PSICQUIC you will learn how to: ● Fetch molecular interaction data programmatically through PSICQUIC; ● Use PSICQUIC view to query multiple databases, not just IntAct. Summary ● PSICQUIC allows to access multiple molecular interactions resources in the same way; ● Access is available via SOAP and REST; ● Different standard formats can be obtained; ● Clients exist to get data from any of the services without having to write custom code; ● It is a community effort. Exercises Exercise 1: Accessing PSICQUIC via REST In the next chapter we are going to talk about the PSIMITAB format in more detail. This exercise only requires a web browser, as we are just going to build some URL to handle specific cases. The figure 3.1. (below) illustrate how to build a PSICQUIC REST URL:
- 19. Question 3: Is it the same to search with the query species:human and with the query species:9606? Can you guess why? Question 4: Could you retrieve the first 10 binary interactions for human (taxid 9606) in IntAct? Exercise 2: Using PSICQUIC View The PSICQUIC view is an example of application that uses PSICQUIC behind the scenes to query many services at the same time. It can be found at: http://www.ebi.ac.uk/Tools/webservices/psicquic/view Question 1: Now that we got rid of those funny URLs, you can try the difference between species:human and species:9606 using PSICQUIC View. The differences can be seen more clearly now. DIP is a clear example. Could you explain what is happening? The PSICQUIC Registry Learning objectives In this chapter you will learn how to: ● use the PSICQUIC Registry to get a list of available services; ● get specific information from the services; ● access the Registry with a browser; ● use the existing Java client to access the Registry programmatically; ● filter services by name or tag.
- 20. The Registry can be found at: http://www.ebi.ac.uk/Tools/webservices/psicquic/registry/registry?action=STATUS Help For further help and information on the query syntax used by the Registry check this URL: http://code.google.com/p/psicquic/wiki/Registry Summary ● The PSICQUIC Registry is a web resource that contains a list of publicly available PSICQUIC services. ● Different information, such as the name, URLs and interaction counts can be obtained. ● The Registry can be accessed programmatically. ● A Java client exists. Exercises Exercise 1: Direct access to the Registry The registry can be access directly using a browser. Question 1: How many services are available? Question 2: Could you get the same list in XML format? Question 3: Could you get the XML information only for the IntAct Service (filter the other services)? Exercise 2: Programmatic access to the Registry This exercise requires the use of the Java registry client. Additional information about the client, including how to include it in your projects, can be found at: http://code.google.com/p/psicquic/wiki/RegistryJavaClient Question 1: Could you list all the PSICQUIC Services and print its name in the console? intact.exercise.chapter4.exercise2.Q1_ListingAllServices Question 2: Like in the previous question, but could you print the count of interactions and the REST URL examples as well? intact.exercise.chapter4.exercise2.Q2_ListingAllServices
- 22. PSICQUIC Java clients Learning objectives In this chapter you will learn how to retrieve data programmatically by using: ● the PSICQUIC Simple client; ● the PSICQUIC Universal client. PSICQUIC Java clients Slides: PSICQUIC Java clients PSICQUIC Client Simple Universal Java lib dependencies None Many Protocol used REST SOAP Streaming Yes No Pagination Yes Yes Integration with model None (but easily integrated) Full integration with XML and MITAB models Speed Faster Slower (due to response generation) Bandwidth Smaller Larger (SOAP evelope and response) Compression Available using specific format Yes Compatibility PSICQUIC 1.1 or higher PSICQUIC 1.0 or higher Help For further help and information about the PSICQUIC Java clients check this URL: http://code.google.com/p/psicquic/wiki/JavaClient
- 23. Summary ● Two available Java clients exist: Simple and Universal. ● The Simple is a nofrills client, just wrapping the REST URL and returning the results as a stream. ● The Universal is the original client and more complex. It is based on SOAP and returns the results in a fullyfledged object model. ● A combination of the Simple and the MITAB library is recommended for maximum performance and flexibility. Exercises Exercise 1: Using the PSICQUIC Universal client Question 1: Could you write the code to query the interactions for brca2 from IntAct and print the identifiers for molecule A and B in the console? intact.exercise.chapter5.exercise1.Q1_PsicquicQuery Question 2: Access with SOAP to PSICQUIC services has a hard limit of 200 interactions per query. Could you write some code to get all the interactions for pubmed 16189514 from IntAct , which contains more than 2700 interactions? intact.exercise.chapter5.exercise1.Q2_ProcessLargeDatasets Information You will need to write a loop to paginate the results and get them in batches. Exercise 2: Using the PSICQUIC Simple client Question 1: Could you write the code to download a MITAB stream from PSICQUIC using the simple client? Print the MITAB for the publication with pubmed 16189514 from IntAct in the console. intact.exercise.chapter5.exercise2.Q1_SimplePsicquicQuery Question 2: If you wanted to count the results for the above query before loading the data, what could you do? intact.exercise.chapter5.exercise2.Q2_CountSimplePsicquicQuery
- 25. PSICQUIC Service Provider Learning objectives In this chapter you will learn how to: ● Create your own PSICQUIC service; ● Start the service locally on the fly; ● Search some data on your custom service. Create a PSICQUIC Service with your data There exists a PSICQUIC Reference Implementation (RI) to simplify the installation of new PSICQUIC Services. The RI just requires a MITAB file as data source, which will be indexed and made available as a service. Help How to install a PSICQUIC Service? Detailed installation steps can be found at the PSICQUIC project wiki: http://code.google.com/p/psicquic/wiki/HowToInstall Summary ● A custom PSICQUIC service with your data is straightforward to install thanks to the Reference Implementation; ● MITAB data is indexed and made available as a web service. Exercises You will need to have the MITAB data to create the service in a file. For example: Question 1: Could you create a file using PSICQUIC with all the interactions for the publication 16189514 from IntAct in MITAB format? We will use this data in our PSICQUIC Service. To create the Service you can follow these steps:
- 26. Steps 1. Download and untar the Reference Implementation with the following commands: wget http://psicquic.googlecode.com/files/psicquicws1.1.6src.tar.gz tar xfz psicquicws1.1.6src.tar.gz cd psicquicws1.1.6 2. Index your file using the RI, replacing <MITAB_FILE> with the name of your file. We will pass as well the path to the index to be created (e.g. /tmp/mypsicquicindex). This index will be essential for PSICQUIC as it will contain all the needed data. After running this, the MITAB file could be discarded. mvn clean compile P createIndex D psicquic.index=/tmp/mypsicquicindex D hasHeader=false D mitabFile=<MITAB_FILE> 3. You should see a BUILD SUCCESS from Maven message after a few seconds. 4. Start the service on the fly using Jetty, using the path to the index:: mvn jetty:run D psicquic.index=/tmp/mypsicquicindex 5. Once the message [INFO] Started Jetty Server appears it means that the server is available. Don’t stop it (e.g. with Control+C) 6. Open a browser and navigate to http://localhost:8080/psicquicws/webservices/ . If you see a list of the SOAP and REST services, everything is working fine. 7. The URL http://localhost:8080/psicquicws/webservices/current/search/query/*, for instance, will show all the data in your service. Question 2: Using the browser, how many interactions are present in your service for the query P25786? Information If you were an experimentalist or a provider and wanted your service to be publicly available by everybody you would just need to request inclusion into the Registry.
- 27. PSIMI XML Learning objectives ● Manipulate PSIMI XML data using the existing Java library; ● Create binary interactions from complexes by using an Spoke expansion algorithm. Introduction to PSIMI XML Slides: PSIMI XML Help More information about the PSIMI XML fomat can be found at http://code.google.com/p/psimi/wiki/PsimiXMLSpecifications The sources and Java library can be downloaded from: http://code.google.com/p/psimi/ Summary ● The PSIMI XML library can be used to read and write XML files. ● It contains a model to represent the interaction data. ● Complexes can be properly represented in PSIMI XML, like in the IntAct model. Exercises Sample files will be provided in each exercise class. Exercise 1: Reading PSIMI XML files Question 1: Could you use the psidev.psi.mi.xml.PsimiXmlReader to read a data file? Iterate through the interactions in the file and print some information. intact.exercise.chapter7.exercise1.Q1_ReadWholeFile Question 2: What do you think it could be a limitation in the approach taken in Question 1?
- 28. Question 3: You can read files in a memoryefficient way by using the psidev.psi.mi.xml.PsimiXmlLightweightReader, which internally indexes the file to read one interaction at a time. Could you write a class using this reader and printing some information about the interactions in the file? intact.exercise.chapter7.exercise1.Q3_ReadIndexedFile Question 4: Could you list the participants of the interactions from a file, and their respective roles? intact.exercise.chapter7.exercise1.Q4_ListParticipantsAndRole Exercise 2: Writing PSIMI XML files Question 1: Could you write an EntrySet to a file by using the psidev.psi.mi.xml.PsimiXmlWriter? intact.exercise.chapter7.exercise2.Q1_WriteToFile Exercise 3: Validating XML files A web resource for PSIXML file validation exists. It can be found at: http://www.ebi.ac.uk/intact/validator Steps 1. Go to http://www.ebi.ac.uk/intact/validator; 2. In the Upload PSIMI XML 2.5 data press on the button “Choose File” and select the file produced in the Exercise 2; 3. Click the “Validate” button and wait for the results. Question 1: Is the file generated in the previous exercise valid? Question 2: If we change the validation scope to IMEx using the radio button selector, is the file still valid? Exercise 4: Using expansion algorithms The PSIMI XML Java library contains a class with different implementations of expansion algorithms, all implementing the psidev.psi.mi.tab.expansion.ExpansionStrategy interface: ● Spoke expansion: psidev.psi.mi.tab.expansion.SpokeExpansion ● Matrix expansion: psidev.psi.mi.tab.expansion.MatrixExpansion ● Spoke without bait expansion: psidev.psi.mi.tab.expansion.SpokeWithoutBaitExpansion
- 32. Course summary In this course you should have learned the following: ● That there are standard formats and tools to gather molecular interaction data; ● These standards have good library support in Java; ● That beyond IntAct, many other database expose their data through PSICQUIC; ● You should feel confident to use data currently available online and use it in the context of your own work. Further reading 1. Orchard, S., Kerrien, S., Jones, P., Ceol, A., ChatrAryamontri, A., Salwinski, L., Nerothin, J., Hermjakob, H. (2007) Submit your interaction data the IMEx way: a step by step guide to troublefree deposition. 7 Suppl 1, 2834 2. Orchard, S., Salwinski, L., Kerrien, S., MontecchiPalazzi, L., Oesterheld, M., Stümpflen, V., Ceol, A., Chatraryamontri, A., Armstrong, J., Woollard, P., et al. (2007) The Minimum Information required for reporting a Molecular Interaction Experiment (MIMIx) Nat. Biotechnol, 25, 894898 3. Kerrien, S., Orchard, S., MontecchiPalazzi, L., Aranda, B., Quinn, A.F., Vinod, N., Bader, G.D., Xenarios, I., Wojcik, J., Sherman, D., et al (2007) Broadening the horizonlevel 2.5 of the HUPOPSI format for molecular interactions. BMC biology, 5, 44 4. Blake, J.A., Harris, M.A. (2008) The Gene Ontology (GO) project: structured vocabularies for molecular biology and their application to genome and expression analysis. Current protocols in bioinformatics, 7, 7.2 5. The UniProt Consortium (2009) The Universal Protein Resource (UniProt) 2009. Nucleic acids research, (37), d169174 6. Degtyarenko, K., Hastings, J., de Matos, P., Ennis, M. (2009) ChEBI: an open bioinformatics and cheminformatics resource. Current protocols in bioinformatics 14, 14.9 7. Hubbard, T.J., Aken, B.L., Ayling, S., Ballester, B., Beal,K., Bragin,E., Brent, S., Chen,Y., Clapham,P., Clarke, L. et al (2009) Ensembl 2009. Nucleic acids research 37, D6907 8. Tateno, Y. (2008) International collaboration among DDBJ, EMBL Bank and GenBank. Tanpakushitsu kakusan koso. Protein, nucleic acid, enzyme 53, 182189 9. Hunter, S., Apweiler, R., Attwood, T.K., Bairoch, A., Bateman, A., Binns, D., Bork, P., Das, U., Daugherty, L., Duquenne, L. et al. (2009) InterPro: the integrative protein signature database. Nucleic acids research 37, D211215 10. Kerrien, S., AlamFaruque, Y., Aranda, B., Bancarz, I., Bridge, A., Derow, C. , Dimmer, E. , Feuermann, M., Friedrichsen, A., Huntley, R., Kohler, C., Khadake, J., Leroy, C., Liban, A., Lieftink, C., MontecchiPalazzi, L., Orchard, S., Risse, J., Robbe, K., Roechert, B., Thorneycroft, D., Zhang, Y., Apweiler, R. and Hermjakob, H. (2007) IntActopen source resource for molecular interaction data. Nucleic acids research 35, d561565
- 33. Where to find our more PSICQUIC Discussion Group: http://groups.google.com/group/psicquic Contributors Version 1.0 of this document: ● Bruno Aranda (baranda@ebi.ac.uk) ● Sandra Ochard (orchard@ebi.ac.uk) ● Samuel Kerrien (skerrien@ebi.ac.uk)
- 35. Chapter 2 answers: PSIMITAB Exercise 1: Programmatic Access using the command line Question 1: Using the command line wget, download MITAB data from IntAct and store it in a file called intact.tsv Answer 1: type the command line wget “http://www.ebi.ac.uk/Tools/webservices/psicquic/intac t/webservices/current/search/query/species:human?first Result=0&maxResults=100” O intact.tsv Question 2: Using the grepcommand, count how many interactions involve the protein P03120. Answer 2: The command line cat intact.tsv | grep P03120 | wc l counts 21 MITAB lines
- 36. Exercise 2: using the Java library for MITAB Question 1: Can you write a class that reads a MITAB data file/stream and print out the count of interactions parsed ? Answer 1: See intact.solution.chapter2.exercise2.Q1_ReadWholeFile Question 2: Should you attempt to load the whole content of a data file/stream into memory could cause problems if the volume of data is large. To facilitate this the class psidev.psi.mi.tab.PsimiTabReaderalso allows developers to iterate over the data. Now write an other program (similar to question 2) that implements this more efficient memory management. Answer 2: See intact.solution.chapter2.exercise2.Q2_ClientAndMitabBetterMemory Question 3: Now that we have read the content of a MITAB file/stream, we can attempt to write this content back to a file. Write a program that writes the MITAB content read into a file. Answer 3: See intact.solution.chapter2.exercise2.Q3_WriteToFile Exercise 3: Indexing MITAB data locally using Lucene Question 1: This library offers the possibility to to index a MITAB dataset using Lucene. This enables users to run local MIQL queries, thus easing data processing. Write a program that indexes the provided MITAB data file. Answer 1: See intact.solution.chapter2.exercise3.Q1_IndexMitabFile Question 2: Write a program that queries the local Lucene index to search for interaction evidences involving specific molecules. For instance by uniprot identifier O45406 or pubmed id 17129783. Answer 2: See intact.solution.chapter2.exercise3.Q2_QueryLocalIndexUsingMIQL Question 3: Like MITAB2.6 and higher, the IntAct extended MITAB format does have a column that describe potential complex expansion that may have been applied to generate binary interactions. Write a program that reads an IntAct MITAB file and print the following: ● total count of interactions; ● count of spoke expanded interaction; ● count of experimentaly identified binary interaction (i.e. not expanded). Answer 3: See intact.solution.chapter2.exercise3.Q3_FilterSpokeInteraction
- 37. Chapter 3 answers: PSICQUIC Exercise 1 answers: Direct access to the Registry Question 1: Fetch the interactions for bbc1 in IntAct. Answer 1: http://www.ebi.ac.uk/Tools/webservices/psicquic/intact/webservices/current/search/query/bb c1 Question 2: Count the interactions for human (taxid: 9606) in IntAct . Answer 2: Using MIQL the query to retrieve all human interactions is species:9606. Then, the query to be used: http://www.ebi.ac.uk/Tools/webservices/psicquic/intact/webservices/current/search/query/sp ecies:9606?format=count Question 3: Is it the same to search with the query species:humanand with the query species:9606? Can you guess why? Answer 3: Running these two queries return different number of results: http://www.ebi.ac.uk/Tools/webservices/psicquic/intact/webservices/current/search/query/sp ecies:human?format=count http://www.ebi.ac.uk/Tools/webservices/psicquic/intact/webservices/current/search/query/sp ecies:9606?format=count The explanation of why these two counts are different can be explained by the fact that the query species:human may hit other organisms (e.g. “human papillomavirus”). Hence, it is safer to use species:9606 if you want to be really specific to that organism. Question 4: Could you retrieve the first 10 binary interactions for human (taxid 9606) in DIP? Answer 4: To do so, the pagination parameters firstResultand maxResultscan be used: http://imex.mbi.ucla.edu/psicquicws/webservices/current/search/query/species:9606?firstR esult=0&maxResults=10
- 38. Exercise 2 answers: Using PSICQUIC View Question 1: Now that we got rid of those funny URLs, you can try the difference between species:human and species:9606using PSICQUIC View. The differences can be seen more clearly now. DIP is a clear example. Could you explain what is happening? Answer 1: DIP stores its human interactions using the scientific name “Homo sapiens”, instead of the common name “human” that IntAct uses. Each provider prepares their own data for PSICQUIC, which can lead to some discrepancies on what data to show. The service providers are collaborating to reach a common agreement to what information should be at least present, hence increasing the compatibility of some specific searches. In our case, searching for species:9606will always return better results as everybody uses the taxid. Chapter 4 answers: The PSICQUIC Registry Exercise 1 answers: Direct access to the Registry Question 1: How many services are available? Answer 1: 16 Question 2: Could you get the same list in XML format? Answer 2: http://www.ebi.ac.uk/Tools/webservices/psicquic/registry/registry?action=STATUS&format= xml Question 3: Could you get the XML information only for the IntAct Service (filter the other services)? Answer 3: http://www.ebi.ac.uk/Tools/webservices/psicquic/registry/registry?action=STATUS&format=x ml&name=IntAct Exercise 2 answers: Programmatic access to the Registry Question 1: Could you list all the PSICQUIC Services and print its name in the console? Answer 1: See intact.solution.chapter4.exercise2.Q1_ListingAllServices Question 2: Like in the previous question, but could you print the count of interactions and the REST URL examples as well?