Course on Functional Analysis
::: Gene Set Enrichment Analysis - GSEA Madrid, Feb 16th, 2009.
Gonzalo Gómez, PhD.
ggomez@cnio.es
Bioinformatics Unit
CNIO
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge Analysis
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge
Analysis
::: Introduction.
Gene Set Enrichment Analysis - GSEA -
GSEA
MIT
Broad Institute
v 2.0 available since Jan 2007
v 2.0.1 available since Feb 16th 2007
Version 2.0 includes Biocarta, Broad Institute,
GeneMAPP, KEGG annotations and more...
Platforms: Affymetrix, Agilent, CodeLink, custom...
(Subramanian et al. PNAS. 2005.)
::: Introduction.
Gene Set Enrichment Analysis - GSEA -
::: How works GSEA
GSEA applies Kolmogorov-Smirnof test to find assymmetrical distributions for defined
blocks of genes in datasets whole distribution.
Is this particular Gene Set enriched in my experiment?
Genes selected by researcher, Biocarta pathways, GeneMAPP sets,
genes sharing cytoband, genes targeted by common miRNAs
…up to you…
::: Introduction.
Gene Set Enrichment Analysis - GSEA -
::: K-S test
The Kolmogorov–Smirnov test is used to determine whether two underlying one-dimensional probability distributions differ, or whether
an underlying probability distribution differs from a hypothesized distribution, in either case based on finite samples.
The one-sample KS test compares the empirical distribution function with the cumulative distribution functionspecified by the null hypo
The main applications are testing goodness of fit with the normal and uniform distributions.
The two-sample KS test is one of the most useful and general nonparametric methods for comparing two samples, as it is sensitive to
in both location and shape of the empirical cumulative distribution functions of the two samples.
Dataset distribution
Number of genes
Gene set 1 distribution
Gene set 2 distribution
Gene Expression Level
::: Introduction.
Gene Set Enrichment Analysis - GSEA -
ClassA
::: How works GSEA
ClassB
FDR<0.05
...testing genes independently...
ttest cut-off
FDR<0.05
Biological meaning?
::: Introduction.
Gene Set Enrichment Analysis - GSEA -
::: How works GSEA
-
ClassA ClassB
Gene
Set 1
Gene
Set 2
Gene
Set 3
Gene set 3
enriched in Class B
ES/NES statistic
ttest cut-off
Gene set 2
enriched in Class A
+
::: Introduction.
Gene Set Enrichment Analysis - GSEA -
ES examples ::
::: Introduction.
Gene Set Enrichment Analysis - GSEA -
The Enrichment Score
NES
pval
FDR
Benjamini-Hochberg
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge Analysis
::: GSEA software.
Gene Set Enrichment Analysis - GSEA -
Download ::
http://www.broad.mit.edu/gsea/
::: GSEA software.
Gene Set Enrichment Analysis - GSEA -
Main Window ::
::: GSEA software.
Gene Set Enrichment Analysis - GSEA -
Loading data ::
!!!
::: GSEA software.
Gene Set Enrichment Analysis - GSEA -
Running GSEA :
::: GSEA software.
Gene Set Enrichment Analysis - GSEA -
Leading Edge Analysis
::: GSEA software.
Gene Set Enrichment Analysis - GSEA -
MSigDB :::
Chip to Chip
Mapping :::
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge Analysis
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Expression datasets
*.gct
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Expression datasets
*.res
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Expression datasets
*.pcl
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Expression datasets
*.txt
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Phenotype datasets
*.cls
For categorical phenotypes (e.g. Tumor vs Control)
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Phenotype datasets
For continuous phenotypes (e.g. Gene correlated to
GeneSet)
Time serie (each 30 minutes)
Peak profile wanted
For continuous phenotypes (e.g. Gene vs Time
Series)
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Gene Set Database
*.gmx
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Gene Set Database
*.gmt
::: Data Formats.
Gene Set Enrichment Analysis - GSEA -
Ranked list format ::
*.rnk
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge Analysis
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Loading data ::
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Loading data ::
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Running GSEA :
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
::: MSigDB.
gsea_home
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Running GSEA :
1. Choose true (default) to have GSEA collapse each probe set in your expression dataset
into a single gene vector, which is identified by its HUGO gene symbol. In this case, you are
using HUGO gene symbols for the analysis. The gene sets that you use for the analysis must
use HUGO gene symbols to identify the genes in the gene sets.
2. Choose false to use your expression dataset "as is." In this case, you are using the probe
identifiers that are in your expression dataset for the analysis. The gene sets that you use for
the analysis must also use these probe identifiers to identify the genes in the gene sets.
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Running GSEA :
Phenotype
Gene Sets (few samples)
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Running GSEA :
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Chip2Chip mapping
Chip2Chip translates the gene identifiers in a gene sets from HUGO gene
symbols
to the probe identifiers for a selected DNA chip.
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Enrichment statistic :
To calculate the enrichment score,
GSEA first walks down the ranked
list of genes increasing a running-sum
statistic when a gene is in the gene set
and decreasing it when it is not.
The enrichment score is the maximum
deviation from zero encountered during
that walk. This parameter affects the
running-sum statistic used for the
analysis.
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Ranking Metric :
Signal2Noise
tTest
Cosine
Euclidean
Manhatten
Pearson (time series)
Ratio of Classes
Diff of Classes
Log2_Ratio_of_Classes
Categorical phenotypes
Continuous phenotypes
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Ranking Metric :
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Ranking Metric :
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
More parameters :
real abs
8.2
8.1
8.0
…
-7.5
-7.7
-7.9
8.2
8.1
8.0
7.9
7.7
7.5
…
parameter to determine whether to sort
the genes in descending (default) or
ascending order.
::: Using GSEA.
Gene Set Enrichment Analysis - GSEA -
Launching Analysis ::
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge Analysis
::: GSEA output.
Gene Set Enrichment Analysis - GSEA -
By default in gsea_home
C:\Documents and settings\username\gsea_home
/Users/yourhome/gsea_home
Results Accession
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge Analysis
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Index.html :::
Heat map of the top 50 features for each phenotype and a plot showing
the correlation between the ranked genes and the phenotypes. In a heat
map, expression values are represented as colors, where the range of colors
(red, pink, light blue, dark blue) shows the range of expression values
(high, moderate, low, lowest).
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Enrichment results in html :
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Enrichment results in html :
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Enrichment results in html :
How can I decide about my results?
FDR ≤ 0.25
NOM p-val ≤ 0.05
::: Contents.
1.
2.
3.
4.
5.
6.
7.
Introduction.
GSEA Software
Data Formats
Using GSEA
GSEA Output
GSEA Results
Leading Edge Analysis
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Leading Edge Analysis
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Leading Edge Analysis
HeatMap
Set-to-Set
Histogram
Gene in Subsets
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Leading Edge Analysis
Heat Map
The heat map shows the (clustered) genes in the leading edge subsets. In a heat map, expression values are represented as c
where the range of colors (red, pink, light blue, dark blue) shows the range of expression values (high, moderate, low, lowest).
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Leading Edge Analysis
Set-to-Set
The graph uses color intensity to show the overlap between subsets: the darker the color, the greater the overlap between the su
When you compare a leading edge subset to itself, its members completely overlap so the corresponding cell is dark green.
When you compare two subsets that have no overlapping members, the corresponding cell is white.
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Leading Edge Analysis
Gene in Subsets
The graph shows each gene and the number of subsets in which it appears.
::: GSEA results.
Gene Set Enrichment Analysis - GSEA -
Leading Edge Analysis
Histogram
The last plot is a histogram, where the Jacquard is the intersection divided by the union for a pair
of leading edge subsets. Number of Occurrences is the number of leading edge subset pairs in a
particular bin. In this example, most subset pairs have no overlap (Jacquard = 0).
::: GSEA & FatiScan.
Gene Set Enrichment Analysis - GSEA -
Detects significant functions with Gene Ontology InterPro motifs, Swissprot KW
and KEGG pathways in lists of genes ordered according to differents characteristics.
::: GSEA & Whichgenes.
http://www.whichgenes.org
- Retrieve miRNAs targets for Gene Set Enrichment Analysis (miRBase, TargetScan)
- Always updated !
Enter if you simply
want to download
gene sets.
Login whether you
want to download
and store your gene
sets
::: GSEA & Whichgenes.
http://www.whichgenes.org
Create Sets
1. Choose oraanism.
-Human
- Mouse
Looking for examples
?
2. Select source:
- miRBase, TScan
- Other sources
3. Copy and paste
miRNAs identifiers.
Create set per
items.
4. Job name.
Retrieving targets
::: GSEA & Whichgenes.
http://www.whichgenes.org
Gene Sets Cart
1. Choose gene sets
for downloading.
2. Select output format.
e.g. .CSV, .TSV, .gmt, .gmx
3. Select identifier.
e.g. Agilent, Affy, Mgi…
4. DOWNLOAD
GENE SETS !!!
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ggomez@cnio.es
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