Lecture 5 - Blast2GO

29.09.2009 – Stefan Götz, Valencia

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Lecture 5

Functional Analysis with Blast2GO Enriched functions

− FatiGO− Babelomics

FatiScan

Kegg Pathway Analysis Functional Similarities B2G-Far


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Biosynthesis 60% Biosynthesis 20%

Sporulation 20% Sporulation 20%

One Gene List (A) ‏ The other list (B) ‏

Are this two groups of genes

carrying out different

biological roles?

84No biosynthesis

26Biosynthesis

BAGenes in group A have significantly to do with biosynthesis, but not with sporulation.

We can do this for each GO, miRNA, InterPro , ... !!!

Fisher's Exact TestC

on

ti

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en

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t

ab

le


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Multiple testing correction

Many tests → Many false positive = we need correction!

FDR control is a statistical method used in multiple hypothesis testing to correct for multiple comparisons. In a list of rejected hypotheses, FDR controls the expected proportion of incorrectly rejected null hypotheses.

FWER control: The familywise error rate is the probability of making one or more false discoveries among all the hypotheses when performing multiple pairwise tests. (more conservative)


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Different types of comparisons

Compare one condition against another

Remove Common Ids Test and Ref-Set are

interchangeable

Set 1 Set 2

Common IDs

Compare a subset against the total

Gossip default setting Test and Ref-Set are

NOT interchangeable

Test-Set

Ref-Set

Common IDs

Test-Set

Ref-Set

Common IDs


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FatiGO in Blast2GO

Two-Tailed test not only identifies over but also under represented functions.

If no Ref-Set is chosen all annotations are used as reference


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FatiGO in Blast2GO Result table with link outs to sequence lists


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FatiGO in Blast2GO

Retains only the lowest, most specific enriched term per GO branch


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FatiGO in Blast2GO Export enriched terms data as DAG graphs!

reduce

=> To draw all nodes, set filter to 1


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FatiGO in Blast2GO

=> Filter results

% of sequences in Ref group

% of sequences in Test group

If Test > Ref = over-expressed

If Ref > Test = under-expressed

Export enriched terms as chart!


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Outline Enriched functions

− Fatigo− Babelomics

e.g: FatiScan


Export annotations to other tools

C04018C10 GO:0004707C04018C10 GO:0006468C04018C10 GO:0005524C04018C10 EC:2.7.11.24C04018E10 GO:0005739C04018E10 GO:0009536C04018A12 GO:0009056C04018C12 GO:0004869C04018C12 ...


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BabelomicsWEB tools suite

A complete suite of web tools for the functional analysis of groups of genes in high-throughput experiments


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BabelomicsKey features

Functional profiling by functional enrichment method (FatiGO) and gene set method (Fatiscan)

Many functional and regulatory definitions (GO, KEGG, Biocarta, text-mining derived bioentities, Transcription factors, CisRed, miRNAs, InterPro, etc.)

Wide coverage of model organisms (more than 10 species)

Import your own annotations


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Babelomics Tools

FatiGO: Finds differential distributions of functional terms between two groups of

genes, these terms can be: Gene Ontology , InterPro motifs, SwissProt KW ,

transcription factors (TF), gene expression in tissues, bioentities from

scientific literature, cis-regulatory elements CisRed.

Tissues Mining Tool: compares reference values of gene expression in

tissues to your results.

MARMITE: Finds differential distributions of bioentities extracted from PubMed

between two groups of genes.

FatiScan: detect significant functions with Gene Ontology, InterPro motifs,

Swissprot KW and KEGG pathways in lists of genes ordered according to

differents characteristics.

MarmiteScan: Use chemical and disease-related information to detect related

blocks of genes in a gene list with associated values.

twolists

ranked list

http://babelomics.bioinfo.cipf.es/tissues/cgi-bin/tissues.cgi

http://babelomics.bioinfo.cipf.es/text_mining/cgi-bin/text_mining.cgi

http://babelomics.bioinfo.cipf.es/marmitescan/cgi-bin/marmitescan.cgi


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Babelomics Databases

Babelomics

Interpro

Gene Ontology

KEGGEnsembl

SwissProt

Transcription Factors

MicroRNA

Cisred

BioentitiesLiterature

Integrated Biological DBof Functional Annotation for more than 10 species


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BabelomicsFatiscan features

Interpret a ranked list of genes There is not need for choosing a cut-off (all

information is included) One statistical test for each Functional Block of

annotation− Multiple testing context (hundreds of annotation)− Filtering of annotation is convenient (the less tests

the best correction)


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FatiScan...testing along an ordered list

• Index ranking genes according to some biological aspect under study.

• Database that stores gene class membership information.

• FatiScan searches over the whole ordered list, trying to find runs of functionally related genes.

List of genes

+

-

Annotation label A

Annotation label B

Annotation label CBA C

Block of genes enriched in the annotation A

Annotation C is homogeneously

distributed along the list

Block of genes enriched in the annotation B


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FatiScan Web Tool

List of genes

C04018C12 2.31C04018C13 2.23C04018C14 1.87C04018C16 1.62C04018E18 0.87C04018E19 0.12C04018A21 -0.01C04018C33 -0.18C04018C65 ....

C04018C13 GO:0004707C04018C14 GO:0006468C04018C15 GO:0005524C04018C16 EC:2.7.11.24C04018E17 GO:0005739C04018E18 GO:0009536C04018A19 GO:0009056C04018C22 GO:0004869C04018C32 ...

List of annotations


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FatiScangene set enrichment analysis (fold-change case-control)

Ran

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(

-.....

GO1 GO2 GO10.... GO11

A:Functional labels (GO, KEGG, etc.) over-represented among over-expressed genes

B:Functional labels under-represented among over-expressed genes

C: Functional labels over-represented among under-expressed genes

D:Functional labels under-represented among under-expressed genes

+

A

B

C D


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FatiScan ResultsSignificantly enriched GO-Terms

Percentages (Test/Ref)

Adjusted p-Values

p-Values


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Functional Analysis - Outline

Enriched functions− FatiGO− Babelomics

FatiScan



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KEGG: Kyoto Encyclopedia of Genes and Genomes

GO Term

EnzymeCode

KEGGPATHWAY


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Obtain Enzyme Codes


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KEGG Pathways

First, choose a folder to save the KEGG maps

Maps are retrieved online Export as text file (tab-sep)


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KEGG Pathways

--> Each enzyme in a different color --> Pathways are ordered for abundance

Or

de

re

d

Li

st


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Functional Analysis - Outline

Enriched functions− FatiGO− Babelomics

FatiScan



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Compare annotation-sets by graphs

We have several conditions, tissues, statistical methods → different sets of annotations

Question: How similar are they? Approach:

Superpose its GO-graphs B2G Solution:

Generate a .annot file with thedifferent conditions as Seq-Name


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Compare annotations by graphs Make a combined graph:


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How to compare two sets of annotations?

Sequence X - original annotations:GO:0045449GO:0009651GO:0005634GO:0003677

Sequence Y - transferred/new annotations:GO:0031323 -> process -> regulation of cellular meta...GO:0043157 -> process -> response to cation stressGO:0005634 -> component -> nucleusGO:0003723 -> function -> RNA binding

-> process -> regulation of transcription-> process -> response to salt stress-> component -> nucleus-> function -> DNA binding

parent (dist2)child (dist1)exact (dist0)

brother (dist2)

similarity

???????????

dissimilarity

How to quantify the similarity of to sets of annotations


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Measures (dis)similarity

5 groups of matches− “Identical” if the B2G annotation

is present among the original annotations of the sequence.

− “General” if the B2G annotated GO term is a parent term of one of the original annotations of the sequence.

− “Specific” if the B2G annotated GO term is a children term of one of the original annotations of the sequence

− "Other branch" if no original annotation terms lay in the same DAG branch of the considered B2G annotated GO term

− "Other Type" if the term can not be compared to any other term because the GO category is not present in the original gene product annotation.


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Use-Case: Compare annotations DBs

Blast2GO function: Search one set of annotations in another

Example: Annotation of 1100 sequences against NR (873 seqs, 3152 annots) and SwissProt (639 seqs, 4547 annots)

Results: Search SwissProt vs. NR annotation:Compared sequences: 610Compared annotations: 4402Swissprot has: Exact GOs:1313 - 30% More specific GOs: 499 - 11% More general GOs: 206 - 5% Other branch GOs: 1660 - 37% Other Type GOs: 724 - 16%

Compare NR vs. SwissProt annotation:Compared sequences: 610Compared annotations: 2488NR has: Exact GOs: 1313 - 53% More epecific GOs: 224 - 9% More general GOs: 387 - 15% Other branch GOs: 405 - 16% Other Type GOs: 159 - 6%


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Functional Analysis - Outline Enriched functions

− FatiGO− Babelomics

FatiScan



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B2G-FAR


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Hundreds of species now with Blast2GO protein

annotations


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Search your sequences in B2G-FAR

Download annotations of your species Load annotations into B2G Deselect all sequences


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B2G-FAR - GeneChips

Lecture 5 - Blast2GO

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Transcript of Lecture 5 - Blast2GO