MDA Blast2GO Exercises

Transcription

1 MDA Blast2GO Exercises Ana Conesa and Stefan Götz March 2011 Bioinformatics and Genomics Department Prince Felipe Research Center Valencia, Spain

2 Contents 1 Annotate 10 sequences with Blast2GO 2 2 Perform a complete annotation process with Blast2GO 3 3 Creating GO-DAGs and Pies 5 1

3 1 Annotate 10 sequences with Blast2GO The aim of this exercise is to annotate 10 sequences following the Blast2GO scheme and to modulate the annotation of these sequences. Open Blast2GO from the application website http: // At the Blast2GO file menu, select the option to Load 10 Example Sequences. Perform the following steps and answer the questions: BLAST against NCBI NR database (do not forget to provide your address). Check the application messages tab to see how the BLAST progresses. How long does it take to complete? Are all sequences successfully blasted? Launch mapping. This is a time-consuming step. While mapping is proceeding, make the following checks: Browse BLAST results for any of the sequences (single sequence menu, right mouse click). Localize different hits and check the local alignment values. As the first mapping result is received, draw the GO graph of mapping results (single sequence menu, right mouse click) and localize annotation scores. Try to understand which GO terms will be annotated. Export top-blast data (at File Menu - Export). Open the file with a SpreadSheet. Compare this information with the information displayed at the Blast results tab. Once mapping is finished: How many GO terms have you fetched for each sequence? Annotate the sequences with the default parameters. How many GO terms do you obtain for each sequence? Generate the annotation graph (DAG) of Sequence 7 (single sequence menu (right mouse click) - Draw graph of mapping results with highlighted annotations). Interpret and save the molecular function graph. Select sequences 1 and 8. Reset annotation of these sequences and re-annotate them at an annotation threshold of 80? How does it change? Bonus questions: There are a number of sequences with mapping but without annotation. What happened? Try to annotate them manually. Tip: go to the Blast results of these sequences to learn about them, decide on the functions you would give to these sequences. Go to the Gene Ontology resource and look for appropriate GO terms. Add these manually to the sequences and mark them as annotated manually. Get InterPro annotation for these sequences. How long does it take? Merge InterPro results with Blast annotations. How much does your annotation improve? Run Annex on these sequences. How does you annotation improve? Get KEGG maps for these sequences. results? For how many sequences do you obtain KEGG Get the GOSlim of these sequences. How many GO terms do you have now? Export annotation results in different formats (.annot, GeneSpring, Sequence Table). Open these files with SpreadSheet. Which format do you like the most? Save your project as.dat file. Create and save 2 subsets of disjoint sequence sets (Tip: use select check-boxes and Delete Sequence Selection function). Close the project. Merge the 2.dat files again using B2G merge function. 2

4 2 Perform a complete annotation process with Blast2GO The aim of this exercise is to perform all steps of analysis for a set of 1100 Citrus clementina sequences. In this way we can learn more about the features Blast2GO offers to get a better understanding of your dataset. Tasks: 1. Download a.dat file of 1100 sequences already blasted against the non-redundant database from the NCBI and mapped against the B2G database: Download: mapping example nr.dat (Alternatively you can download the SwissProt dataset and compare your results with the results of one of your colleagues: mapping example swissprot.dat) 2. Please start Blast2GO with 1024MB of memory and load the.dat file 3. First of all please go to Tools - Database Configuration and check that everything is ok. 4. Perform the Annotation step with default parameters. (in case of a slow Internet connection please download and use the.dat file which is already annotated with default parameters: annotation example nr.dat) 5. Generate now for each Blast2GO step (blast,mapping,annotation) the corresponding statistic charts like e.g.: Blast: e-value distribution, species distribution, similarity distribution Mapping: Evidence code distribution, DB Sources of mapping Annotation: GO annotation level distribution etc. 6. Export some of the charts as.png and.pdf files 7. Import InterProScan XML results to the already annotated sequences and merge the annotations. 8. Download the zipped XMLs (.zip, tar.gz) and unzip them. (Unzip files under Linux with a right mouse click on the file extract here ) 9. Perform the Annex augmentation 10. Now save you project as a.dat file and export the annotations as.annot file. Bonus questions: 1. Perform a GO-Slim reduction and generate again a GO annotation level distribution chart. 2. Change Annotation strategy: (reset the existing annotation) Lets be very restrictive: Set all experimental evidence codes (plus TAS) to 1 (first six ones in Blast2GO) and the rest to 0. Set the annotation rule to 70. Set the e-value filter cut-off to 1E-10. To compensate the restrictive setting we increase the GO-weight to 10. Now redo the annotation step and analyse the results generate a data-distribution chart. Lets be very permissive: Set all evidence codes to 1. Set the annotation rule to 50. Set the e-value filter cut-off to 1E-3. 3

5 Set the GO-weight to 0 to inhibit the abstraction mode and compensate the very permissive settings. 3. Now reset and redo the annotation step and analyse the results generate a datadistribution chart. Open the file blast example swissprot.dat, annotate the set in the way you think it is most convenient and compare the performance with the different annotation styles you applied to the NR-dataset. 2.1 Questions 1. What do we observe about the obtained e-values for this dataset of sequences - and how behave the sequence similarities? 2. Have a look at the mapping charts and try to interpret them. 3. Having a look at the GO annotation level distribution : What is the mean level of all GO-annotations and how many annotations could be assigned. 4. For how many sequences could you obtain a InterPro results and how many of them contributed with GO-Terms. 5. Tell how many more sequences could be annotated by adding the InterProScan GO-terms? 6. How many more annotations could be assigned through the Annex step. 7. Finally, generate the level-distribution chart for the different settings and interpret the results. 8. Can you obtain more/less annotated sequences by modifying the annotation parameters? How? 4

6 3 Creating GO-DAGs and Pies The aim of this exercise is to learn how to create informative GO graphs (DAGs) and how to summarize your data in charts that can be included in a publication. Please use for this exercise the Blast2GO project file containing the 1500 sequences from the NFS Potato microarray 10K. Tasks: Create the complete graphs for all 3 GO branches. Can you extract any conclusion? Use the seq and score filters to reduce the number of GO terms. Try one type of filter at the time. How does the resulting graph look like? Which filtering value gives you a good view on the data? Can you see easily important terms? How? Which ones? Perform a GOSlim on these data (use plant specific). Create the DAG. How does it compare to the previous graphs? Generate pie charts with normal and multilevel pies and bar-charts. Try out different filter settings until you get a useful summary. Which functions are more abundant? Give a summary of the functions represented in this sub-array. Bonus questions: Export the graph-data as plain text file (txt) and open it in Excel (SpreadSheet). Try to reproduce some of the charts you obtained with Blast2GO. Save your charts and DAGs and visualize them outside the application. Make a custom-colored graph with the top 100 GO terms ordered by the amount of annotated sequences. 5