Chronos: NGS database, web service and media

Sun, 03 May 2026 22:20:37 +0400

Chronos is a database of NGS data and a web service that makes it possible to work with this database. The database contains anonymized annotations of patients who have undergone the BostonGene clinical test and their NGS data — mutations, copy number alterations, fusions, expression. The cBioPortal web service allows you to analyze this cohort through your browser.

The user works with Chronos through the cBioPortal web service

The goal of the project is to accelerate and simplify retrospective analysis of patients: this used to be long and painful, and now there is uniform storage, an analysis tool, and instructions on how to use it.

It used to take a long time just to collect the data before starting the analysis. Now you can focus on the analysis itself.

To share news, updates to the database and train users, a Telegram channel was created. For training I recorded short videos and instructions with screenshots. In total about 60 video and text lessons were recorded.

Examples of questions that Chronos helps answer:

how many high‑quality and in‑house sequencing samples does BostonGene have
how to find a sample by mutation or fusion
how to compare double mutants against mutants, for example by microenvironment activity
how to compare groups of patients by gene expression level
how to draw a simple oncoplot and save the picture
how to find co‑expressed genes
how to find differentially expressed genes between two groups
how to find all samples with NTRK fusions
how to find samples with a mutated RAS
how to view germline mutation frequencies

🪣 project bin

In the bin I describe the life cycle of Chronos from an idea in 2021 to implementation. You shouldn’t treat Chronos as a pure work project. It’s a samurai’s path.

Start of the project

BostonGene helps patients by performing deep tumor analysis. Information about analyzed samples accumulates and, from time to time, clinical and research tasks related to this cohort arise. For example, a doctor asks: “What is the frequency of HER2 amplifications in breast cancers among the patients I sent you?”

It was necessary to design a system for storing, accessing and analyzing the collected cohort.

cBioPortal, containerization and deployment

cBioPortal is a service for storing and analyzing annotated NGS data developed at Memorial Sloan Kettering Cancer Center. There is their own portal, which they host on their servers and maintain themselves, and there is a packaged version distributed via GitHub for everyone. You just can’t make money on it because of the license.

I studied the documentation for cBioPortal. It turned out that the developers packed the service into docker‑compose. To deploy it on the company’s server for testing, I studied what containerization and the Docker tool are and in the second week I deployed an empty cBioPortal on the company’s server.

Deployed an empty portal on the company’s server

ETL and the first data in cBioPortal

The next step was to study what ETL is and the layout specification and file formats for loading a cohort into cBioPortal.

ETL (Extract, Transform, Load) is a pipeline for collecting raw data from many sources, filtering out unnecessary stuff, transforming it into the desired format and loading it where needed.

In the third week I uploaded the first annotation, mutations, rearrangements and expression.

Now the portal isn’t empty; annotation, mutations, rearrangements and expression have been added

Relational database, SQL, population and queries to the database

At an early stage we thought that cBioPortal is exactly the tool for cohort analysis with a convenient web interface. And it seemed logical that alongside the analytical tool we needed to create a database from which ETL would then pull data into cBioPortal.

At first I listed what attributes samples and cases have and sketched out a data model that formed the basis of the future database. It turned out, for example, that a patient can have multiple biopsies, and each biopsy can have multiple sequencing runs.

Chronos started with papers and diagrams

While working on the task, I learned what relational databases and PostgreSQL are, the SQL query language and the Python package SQLAlchemy for creating a database schema and interacting with it. I also learned how to populate the database via web forms and the Flask package.

I made a prototype and packed everything into containers using Docker and docker‑compose.

Diagram of the relational database and the web form used to populate the database

Launch of the media and knowledge base

To develop the project further, I needed to understand the real demand in the company for this tool. I created a channel in the messenger and over several months recorded about 60 micro‑instructions and videos on working with cBioPortal, posts about updates and various improvements in the project. As a result, a good internal media for promoting the project and a knowledge base emerged. Demand was confirmed, it’s possible to move on.

Demand confirmed, we can move further.

Delegation of the project

My colleague, bioinformatician Daniil Ivanov, takes over the technical part of the project and I remain the ideologist and promote the project through educational content. Daniil starts a backlog, collects use cases from users, prioritizes tasks, plans the move to Kubernetes, gets rid of the SQL database. He hands the backend and infrastructure to professional developers and dives into operational work with data — ETL, launching pipelines.

A lot of work has been done, but I deliberately do not describe the nuances of technical implementation, because I want to show the life cycle of the project as a whole and not drown in the tech.

Prime

After developers connected the portal began to fully operate, and through the educational channel all this time I tried to warm up the audience. The prime period of Chronos has arrived.

It is used for research tasks and retrospective cohort analysis, helps in hot topics like ADC NECTIN4 and TROP2, abstracts and posters for ASCO and AMP are prepared with it, and the sarcoma cohort has become larger than TCGA. Clinicians look for patients by genetic events, bioinformaticians select samples to validate tools, the director right at the meeting with the client tests hypotheses in cBioPortal.

“Comparative Molecular Analysis of Clear Cell Sarcoma and Cutaneous Melanomas: Key Genetic Insights for diagnosis”. Abstract and poster for the AMP2024 conference, the primary analysis was performed using cBioPortal. BostonGene news.

Decline

Then things calmed down. For six months cBioPortal was used only in one research task and one person left feedback that he uses it in his work.

Despite the noble idea, technical implementation, media and knowledge base, the product faced the reality of business and a strong user habit. The business pivoted and orders for retro analysis disappeared. And for research tasks bioinformaticians use JupiterHub, and we could not overcome this habit even after two years of media and cBioPortal workshops.

In 2026 Chronos is experiencing a decline. cBioPortal still works, the cohort is updated every month, but the requests are few. On the other hand the project is already so autonomous that it needs improvements and constant supervision less. So that’s fine.

Konstantin Chernyshov: posts tagged 2021