Gonzalo Gómez, PhD. ggomez@cnio.es

Madrid, June 31st, 2007.

::: The Connectivity Map - cMap -

Course on Functional Analysis

Bioinformatics Unit CNIO

The Connectivity Map - cMap -

::: Introduction.

MIT Broad Institute

164 small molecules loaded

10nm, 100nm, 1 µM, 10 µM 6 & 12 hours treatment

Breast, prostate, leukemia and melanoma cell lines

cMap

Lamb et al. Science 29 September 2006:

Vol. 313. no. 5795, pp. 1929 - 1935

The Connectivity Map - cMap -

::: Introduction.

cMap applications :::

A hypotheses generating tool

The Connectivity Map - cMap -

::: Introduction.

Example :::

Molecular signature strongly induced by

drug A

Molecular signature weakly induced by

drug B

Drug C has no effects on molecular signature

Molecular signature strongly repressed by

drug D.

Perturbagen: Any modality, such as addition of a small molecule or introduction of a genetic reagent (eg shRNA). Perturbagens (or groups of closely related perturbagens) are identified in cmap by their cmap name. A single perturbagen may be represented by multiple instances.

Instances: A treatment and control pair and the list of probe sets ordered by their extent of differential expression between this treatment and control pair. The instance is the basic unit of data and metadata in cmap. Each instance is uniquely identified by an instance_id. Every instance has a number of attributes including a unique identifier ( ie instance_id), the batch in which it was produced, the cmap name of the treatment, the source of that treatment, the concentration of that treatment, the cmap cell line used, and the scan numbers for the treatment and its control(s).

The Connectivity Map - cMap -

::: Introduction.

cMap Nomenclature :::

The Connectivity Map - cMap -

::: Introduction.

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 hypothesis. 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 differences in both location and shape of the empirical cumulative distribution functions of the two samples.

Instance 1 distribution

Num

ber of genes Gene Expression Level

Up tag list distribution

Down tag list distribution

Instance 2 distribution

Num

ber of genes

Gene Expression Level

Up tag list distribution

Down tag list distribution

etc.

The Connectivity Map - cMap -

::: cMap Web Tool.

Accession :::

http://www.broad.mit.edu/cmap/

Registration

The Connectivity Map - cMap - Main Window :::

::: cMap Web Tool.

The Connectivity Map - cMap - Help Tab :::

::: cMap Web Tool.

Quick and tmp

The Connectivity Map - cMap - Query tab :::

::: cMap Web Tool.

Load, store signatures and save results

Preloaded data

Build a internal signature from a number (until 3) of different instances on the fly

The Connectivity Map - cMap - Quick Query :::

For human signatures: NetAffx

For non human signatures: 1)  Homologene (to Unigene) 2)  NetAffx

.grp files HG-U133A identifiers

::: Query Tab.

The Connectivity Map - cMap -

::: .grp Format

Remember Affy HG-U133A identifiers !!!

The Connectivity Map - cMap - Load signature :::

Information about your signature

::: Query Tab.

The Connectivity Map - cMap -

Query tab :::

Multiple Instance Query :::

The Connectivity Map - cMap - Results :::

::: Results Tab.

The Connectivity Map - cMap - Results :::

::: Results Tab.

+ scores

- scores

NULL scores

The Connectivity Map - cMap - Results formats :::

::: Results Tab.

Combined Results Agent (rather than an instance) focus

Permuted results Whole Perturbagen enrichment (set of instances) and p scores

Permutation p

The Connectivity Map - cMap - Scores & p-scores :::

::: Results Tab.

Down Score A high positive down score indicates that the corresponding perturbagen induced the expression of the probe sets in the down tag list. A high negative down score indicates that the corresponding perturbagen repressed the expression of the probe sets in the down tag list. The connectivity score is a combination of the up score and down score.

Up score: A value between +1 and -1 representing the absolute enrichment of a up tag list in a given instance. The up score is the “up” value reported on the result page. A high positive up score indicates that the corresponding perturbagen induced the expression of the probe sets in the up tag list. A high negative up score indicates that the corresponding perturbagen repressed the expression of the probe sets in the up tag list.

Permutation p: An estimate of the likelihood that the enrichment of a set of instances representing a specified perturbagen in the list of all instances in a given result would be observed by chance. This value is determined empirically by computing the enrichment of ten thousand sets of instances selected at random from the set of all instances in the result.

The Connectivity Map - cMap -

::: Results Tab.

Results tools :::

The Connectivity Map - cMap - Interpreting results :::

::: Results Tab.

Induce connection

Reverse connection

NO connection

The Connectivity Map - cMap -

Interpreting results :::

Strong Negative Connection

Signature - Perturbagen

Strong Positive Connection

Signature - Perturbagen

Some examples :::

Not clear connection Signature - Perturbagen

The Connectivity Map - cMap -

Interpreting results :::

Scores :::

High (positive or negative) connectivity scores and low p-scores are diserable.

However …

Strict adherence to p-scores is not recommended because they do not taken into account of the presence of null instances, instances of opposite sign or any instance attribute

The Connectivity Map - cMap -

Interpreting results :::

Running Sum Plot :::

Good separation of the two trajectories and maximum deviation from zero near opposite extremes of the x-axis is desirable when attempting to build confidence in particular hypotheses for challenging signatures. Alternatively, a minor peak at either end of the x-axis implies a strong affect on a portion of the signature. This may be sufficient evidence to call a hit for a complex signature, provided the effect is seen in multiple instances of the same perturbagens.

up tag file

down tag file

Walking--->

The Connectivity Map - cMap - Instances Tab :::

::: cMap Web Tool.

The Connectivity Map - cMap - Admin Tab :::

::: cMap Web Tool.

ggomez@cnio.es

Thanks !!