Navigating the Genomic Data Maze: Essential Tools and Applications by Łukasz Zawada - Sigma IT Navigating the Genomic Data Maze: Essential Tools and Applications by Łukasz Zawada
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Life Science Software development
Genomic Data

Navigating the Genomic Data Maze

Essential Tools and Applications

Genomic data, with its vast complexity and volume, necessitates a structured approach to processing and orchestration. This article delves into the critical components that form the backbone of genomic data processing, highlighting the indispensable tools and applications that streamline this process. To effectively navigate genomics data processing, several key elements come into play. These elements serve as the foundation upon which genomics research and analysis thrive.      

Key Components of Genomic Data Processing

When approaching genomic data processing, it quickly turns out that some types of applications might be required to establish processing and orchestration:

ETLs (Extract Transform Load)

ETLs (Extract Transform Load) are the bread and butter of the data processing. They involve extracting data, applying transformations like file type conversions, moving to virtual clouds, or filtering for relevant information, and finally loading the data. ETLs play a vital role in genomics data processing.

Genomics applications (licensed and open)

Genomics applications (licensed and open) for Quality Checks, gender identification, etc.) which are, in fact, a part of the ETL.

Data exchange points

Data exchange points processing genomic data never occurs in isolation; collaboration with various third parties becomes essential. Whether it’s obtaining data from laboratories or exchanging it for analysis, establishing data-sharing endpoints is crucial.

Visualizations (for visualising effects of genome processing)

Visualizations are pivotal in genome processing, as they reveal the bigger picture and foster innovative ideas. While raw data in the console has its uses, visual representations offer a clearer understanding of the relationships within the data. These visualizations are crucial not only for those who are less comfortable with the CLI, but also for showcasing progress to the public and sharing reports with management.


Commands in CLI or single purpose applications (executors of pipelines, authenticators, various commands that help run workflows by different parties). Helpers, as part of the orchestration layer, do not process data directly. Instead, they facilitate the seamless execution of script functions and handle authorization layers.


In the realm of genomics, data processing and orchestration are the keystones upon which groundbreaking discoveries are built. The complexity and enormity of genomic data necessitate a systematic approach, and the components outlined here – ETLs, genomics applications, data exchange points, visualizations, and helpers – collectively form the framework that supports the relentless pursuit of knowledge within the field. As genomics continues to evolve, these components will remain the bedrock of data processing, ensuring that researchers can navigate the labyrinthine world of genomics information with precision and efficiency.


Software Engineer at Sigma IT Poland
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