8. Data Packages


Only one IC50 files should be provided. It is filtered out according to the genomic feature file.

8.1. Definition

A Data Package is a terminology used to speak about a directory that contains the results of an analysis. For example, the data package called BLCA has a tree directory that looks like:

|-- code
|-- css
|-- images
|-- js

The main directory contains a file named index.html. Many other HTML files may be present but the index is your entry point to browse the content of data package.

The directory css and js contains resources required by the HTML documents.

The INPUT directory contains 3 data files and the settings used during the analysis:

  1. ANOVA_input.csv
  2. DRUG_DECODE.csv
  3. genomic_features.csv
  4. settings.json

See section on Data Format and Readers for details about the data format and the About the settings section.

Finally, the OUTPUT directory contains:

- drugs_summary.csv
- features_summary.csv
- results.csv

The images directory contains a mix of images and HTML for each significant associations.

8.2. Create your own package

In fact, we have already seen how to create a pacakge. This is covered in HTML report when we used the ANOVAReport class but let us look at the code again:

from gdsctools import ANOVA, ic50_test, ANOVAReport
gdsc = ANOVA(ic50_test)
results = gdsc.anova_all()

report = ANOVAReport(gdsc, results)

Here, we have not yet mentionned the type of cancers or tissues since we used a simple genomic feature file but one we need to repeat this analysis across man y different genomic features files. The gdsctools.gdsc.GDSC class will help us for that purpose.

8.3. Create data packages across TCGA

When we do a full GDSC analysis, the cell lines span a set of TCGA tissues (e.g., COREAD, BLCA) and generally we want to perform the analysis not on all cellines at the same time but each type of tissues independently.

Besides, you may then wish to have data packages not only for a given TCGA tissue but also for a given company (if your DrugDecode file is filled properly; see later).

The recommended way is to used the gdsctools.gdsc.GDSC class that will help you in this task.

First, you need to prepare the input data. Create a directory and add these files:

- a unique IC50 file
- The genomic features files for each type of tissues.
- The DrugDecode file

The genomic feature must be named as follows:


The name of the TCGA can include ALL, PANCAN and will be used later to create the directories for each data paakage.

The important point being that there must be an underscore only and followed by the TCGA tag.

The GDSC class will then loop over the TCGA cases and create data packages.

from gdsctools import GDSC
gg = GDSC("IC50.csv", "DrugDecode.csv", "GF_*.csv")

This may take hours to finalise: the ANOVA and creation of all images will be done for each TCGA.

This may be parallelised since each input Genomic Feature analysis is independent:

gg_blca = GDSC("IC50.csv", "DrugDecode.csv", "GF_BLCA.csv")

gg_coread = GDSC("IC50.csv", "DrugDecode.csv", "GF_COREAD.csv")

In an error occurs for one Genomic Feature file, the analysis we jump to the next file. You may need to check re-run the specific TCGA tissue analysis your self when an error occured (meaning you do not need to re-run everything).

Once done, you should have all data packages locally in the directory where you ran the scripts.

The next step is to read back all those results and create data pacakges dedicated to a company. Based on the DRUG_DECODE file:

gg = GDSC("IC50.csv", "DrugDecode.csv", "GF_*.csv")

For each companies, which names can be checked with:


a new directory (data package) is created locally

For now, it is important to run this in the same directory where previous pacakges were created.

Again thiis may be parallelised:

for each company in gg.companies:
    single = GDSC("IC50.csv", "DrugDecode.csv", "GF_*.csv")

8.4. Create summary pages

Following the creating of the “all” TCGA packages and the dedicated packages for all companies, you end up with quite a few directories. This command will create summary HTML page to ease your life:


This must be called after analyse() and create_data_packages_for_companies().