To analyze relationships between perturbations, we utilize the framework of connectivity. A connectivity score between two perturbations quantifies the similarity of the cellular responses evoked by these perturbations. A score of 1 means that these two perturbations are more similar to each other than 100% of other perturbation pairs. A score of -1 means that these two perturbations are more dissimilar to each other than 100% of other perturbation pairs.

Introspect means querying your dataset against itself. Make sure to "Include Introspect" if you would like to see connections within your dataset (in addition to connections between your dataset and Touchstone-P).

In computing connectivity, biological or technical replicates can be aggregated together. Please select which metadata fields should be used to recognize replicates. For example, if you wish to distinguish between different doses of the same compound, make sure to select "pert_dose" (or something similar) as one of the metadata fields by which to group replicates. The possible metadata fields by which to group replicates only appear after you have upload your GCT and selected "Yes" for "Are there replicates in your data?".

Access a suite of analysis apps by clicking on the menu (or type command-K to open)

The first step in using the Query App to compute connections with your gene expression data is to assign a name to your query. Results will be stored in your Analysis History after your query is submitted.

Enter an up-regulated gene of interest, hit enter, and type in subsequent genes in the set you would like to query. You may also have down-regulated genes of interest. They can be entered in the box to the right.

Hit submit and the query algorithm will find connections between your genes of interest and perturbagens in CMap that have signatures most similar to your query. Data are generated in approximately 5 minutes and will be stored in your Analysis History.

The L1000 assay directly measures or infers the expression levels of 12,328 genes. By evaluating the current statistical model against a large compendium of RNA-Seq profiles from over 100 tissues from the GTEx consortium, we have identified a subset of 10,174 genes that are either measured or well inferred. This subset is known as the Best INferred Gene (BING) space. The Query App uses BING space to compute similarities between users' gene sets and the gene expression signatures in the CMap database. Each user entry is therefore mapped into one of the three following categories.
Invalid gene: Not a valid HUGO symbol or Entrez ID, and therefore not used in the query.
Valid gene: A valid HUGO symbol or Entrez ID that is also part of BING space, and therefore is used in the query.
Valid but not used in query: A valid HUGO symbol or Entrez ID that is not part of BING space, and therefore is not used in the query.

Click on a perturbagen in this table to see a CLUE Card that contains all of the information available for this perturbagen. You can also select any compound in the table to query connections with all other compounds in Touchstone. Click on Detailed List to view connections in a table, or click Heatmap to see connections in a matrix powered by the Morpheus App.

Filter the Touchstone data table by selecting perturbagen type or perturbational classes of interest.

Average transcriptional impact

Impact is assessed as a transcriptional activity score, which is calculated as a mean value of median replicate correlation and median signature strength of a perturbagen across multiple cell lines and doses. The score describes a perturbagen’s transcriptional activity, relative to all other perturbagens, as derived from its replicate reproducibility and magnitude of differential gene expression.

PCTCCi =  rank( median( CCi ) )N

PCTSSi =  rank( median( SSi ) )N



TASi is the transcriptional impact score for the i-th perturbagen

PCTCCi is the percentile, relative to all other perturbagens, of the i-th perturbagen’s median replicate correlation coefficient (CC) across all of its signatures

PCTSSi is the percentile, relative to all other perturbagens, of the i-th perturbagen’s signature strength (SS) across all of its signatures

N is the total number of perturbagens

Signature diversity

Thick black bars signify Transcriptional Activity Scores greater than or equal to 0.5; thinner black bars denote scores less than 0.5. Absence of a bar means no data available. Colored lines (chords) signify similar connectivity scores between cell lines; red for positive connectivity scores of 80-100 (pale to intense color according to the score); blue for negative connectivity. Chords are only shown when TAS scores are > 0.5; thus absence of a chord either means that the perturbagen TAS score is very low, or that no data is available. Chords for individual cell lines can be isolated from the rest of the figure by hovering over the cell line name.

Baseline expression of this gene in each cell line is represented as a z-score (top numbers). Scores were calculated using robust z-score formula:

z-scorei = ( xi - median( X ) )/( MAD( X ) * 1.4826 ),


xi is expression value of a given gene in i-th cell line

X = [ x1, x2 ... xn ] is a vector of expression values for a given gene across n cell lines

MAD( X ) is a median absolute deviation of X

1.4826 is a constant to rescale the score as if the standard deviation of X instead of MAD was used

Median and MAD expression values were calculated using RNA-Seq profiles from a total of 1022 cell lines, comprising data from the Cancer Cell Line Encyclopedia (CCLE; Barretina, et al.) and cell lines nominated by the CMap team. Plots show z-score values only for the core LINCS lines used by CMap in L1000 experiments. Light red or light blue regions indicate positive or negative outlier expression, respectively, of the gene relative to the other lines shown; z-score of a positive outlier in the corresponding cell line is in dark red and a negative outlier is in dark blue.

Summary class connectivity shows a boxplot that summarizes the connectivity of a class. Each data point, shown as a light gray dot, represents the median value of connectivity of one member to the other class members. (This corresponds to the median for each row, excluding the main diagonal, in the heatmap shown below.) The box is the distribution of those data points, where the box boundary represents the interquartile range, the vertical line within the box is the median, and the whiskers reflect the minimum and maximum values of the data (exclusive of extreme outliers, which may appear beyond the whiskers).

Connectivity between members of class is a standard heat map of the connectivity scores, summarized across cell lines, between members of the class, where dark red represents the highest positive scores and deep blue the highest negative scores. Individual scores are revealed to the left below the map by hovering over each cell of the map.

Class inter-cell line connectivity is a plot of the median (black line) and Q25-Q75 connectivity scores (blue area around black line) for each cell line as well as the summary scores across cell lines. In some cases perturbations have not been tested in every cell line; the absence of data is indicated by a “0” for that cell line. The example shown reveals that these estrogen agonists show the strongest connectivity to each other in MCF7, a human breast cancer cell line that expresses the estrogen receptor.

Profile status

Colored portion of top bar indicates the Broad assays in which this compound has been profiled.

L1000 cell/dose coverage

For compounds profiled by L1000, cell lines and dose range for which signatures are available are indicated by dark gray bars (lighter gray bar indicates no data is available for that cell line/dose combination). A bar displayed one row above the 10 uM row indicates that doses higher than 10uM were tested. The 6 rows correspond to 6 canonical doses: 20 nM, 100 nM, 500 nM, 1 uM, 2.5 uM, and 10 uM. (In some cases non-canonical doses were tested; these are rounded to the nearest canonical dose for the purpose of this display. For example, if the dose tested was 3.33uM, the 2.5uM bar is shown in dark gray here.)


The CLUE API offers programmatic access to annotations and perturbational signatures in the CMap L1000 dataset via a collection of HTTP-based RESTful web services. These services support complex queries via simple HTTP GET requests that can be executed in a web browser or any programming language. If you are using a web browser to display results, it is best to add your favorite JSON viewer add-on or plugin. The results are returned as standard JSON objects. Click on the links on the side for usage instructions and examples. API requests is based on the loopback framework syntax.

API Access

Registration is required to obtain a user-specific API key. If you already have a clue account and you are signed in, click on your name in the upper right corner, then click on "Account Settings" to find your API Key. The examples below use a limited demonstration key.

Instructions and examples

Cell service

The cell service returns cell line information.


Gene service

The gene service returns meta-information for measured and inferred genes in the CMap L1000 dataset.


Profile service

The profile service returns meta-information for profiles in the CMap L1000 dataset.


Perts service

The pert service returns meta-information for perturbagens in the CMap L1000 dataset.


Plate service

The plate service returns plate information.



The sig service returns meta-information for signatures in the CMap L1000 dataset.


Pertubational Classes

The PCL service returns meta-information for perturbational classes in the CLUE dataset.


Repurposing Hub database

Therep_fda_exclusivity service returns information about the exclusivity period of a given drug. This information was obtained from the FDA Orange Book publication.


Therep_drug_moa service returns information about the mechanism of action of a drug.


Therep_fda_orange-book_term service returns information describing abbreviations used in the Orange Book.


Therep_fda_patent service returns information about the patent of a given drug extracted from the Orange Book.


Therep_sample service returns information about the purity, chemical structure, source, and various textual identifiers of the compound.


Therep_drug service returns information about drug synonyms, clinical status, corresponding FDA Orange Book ingredient(s), and external database identifiers.


Therep_drug_indication service returns information about the indications and disease areas for approved drugs.


Therep_fda_product service returns information about a product extracted from the FDA Orange Book publication.


Therep_drug_target service returns information about the gene target of a compound.


API Playground

The CLUE API playground allows end consumers to visualize and interact with the API's resources/services.

The CLUE API playground allows end consumers to visualize and interact with the API's resources/services.

After you have clicked on the link above, you will reach the CLUE API Explorer page. From here, you want to add your personal API Key. You can do so by clicking on the "Edit API Key" button.

You will notice that there is already an API key there. You want to replace that with your own. To find your personal API Key, head over to and log in to your account. Click on your username and copy and paste the string under the heading "API Key" and paste it in the CLUE API Explorer.

Now, you can interact with the API’s services. For instance, you can click on a field, such as "pert" and a drop down menu will display all of its API endpoints.

To view more, you can click on "GET/perts" for an expansion of additional operations.

This expansion allows you to search in the parameters. Let’s say that you want to query the compound sirolimus. You can do so by typing in this syntax:


Click "Try it out!" to submit this query request.

You will then get a Response Body that shows the information available for your query.