TL;DR: Mantle makes data engineering easy (and sometimes fun) for scientists.
Today, we are excited to announce the launch of Mantle’s free plan, now available to the scientific community. Get started here!
💻 Why does biology need better data engineering?
Biotech generates very big, very complex data. A single DNA sequencing experiment can create 7 TB of data, and generating high-throughput multi-modal data is becoming the norm. Recent breakthroughs in computer science and ML have incredible potential to accelerate life science research.
Electronic lab notebooks (ELNs), like Benchling, help organize research in the wet lab. However, biotech lacks tools to organize and analyze data from instruments, CROs, and public databases.
Does this sound familiar?
- Storing experimental metadata in file paths
- Writing regex scripts to parse metadata out of those file paths
- Regex scripts break when the file path format changes
- Running bioinformatics scripts locally on a laptop
- Not being able to process data when the computational scientist is on vacation
- Losing analyses when the computational scientist loses their laptop on vacation
- Analyzing datasets one by one in a desktop application
- Not being able to compare data between teams because each person made the graph slightly differently
- Spending a weekend regenerating all of the graphs consistently, and finding several copy-and-paste errors made on the data that was submitted to the grant application last week
At Mantle, we think science deserves better.
🔬 What can you do with Mantle?
Instant Insights
Make decisions quickly and confidently. See everything in one place, in real time.
Modern Data Management
Don’t let unscalable spreadsheets and inflexible databases slow down your research. Scientific research requires rapid iteration and experimentation, and Mantle’s data lake can keep up.
Bring Your Code
Effectively leveraging computation, data science, and ML separates the next generation of biotech companies from the last. Mantle hosts the infrastructure to help connect no-code users and great-code writers.
🌎 How does it work?
Mantle is a data infrastructure layer (the “mantle” 🙂 🌎) for biological data analysis.
- Import data from ELNs (e.g. Benchling), instruments (e.g. Illumina), CROs, and more
- Process data reproducibly with bioinformatics pipelines and Jupyter Notebooks
- In a private data lake, find, organize, and analyze data of any type and scale
- Insights are accessible to no-code users through real-time visualizations
- Data Science & ML results can be easily shared and traced back to raw data
Why doesn’t biology use “normal” data engineering tools?
- The data is different. General-purpose tools are designed for consistently structured tabular data. Biology generates data with frequently changing metadata in biology-specific formats. Mantle’s data lake stores data of any scale, format, or type in a single place.
- The ecosystem is different. Tools that are not designed for biology don’t prioritize integrations with other tools in the science ecosystem. Mantle has off-the-shelf integrations with standard life science tools.
- The processing is different. Tabular data can typically be processed with simple transformations. Preprocessing genomics data can take dozens of hours and careful parameter tuning. Custom and off-the-shelf bioinformatics pipelines can be run reproducibly through Mantle, with or without code.
👋 Help us close the gap between data and discovery
We love data engineering, and we love helping scientists. If you’d like to, here are some ways you can help us:
- Give Mantle a try!
- Get started here for free.
- Let us know what you think!
- If you want to chat or see a demo, please reach out to me here: emily@mantlebio.com
- If you would like help debugging a weird AWS error, please reach out to my co-founder here: madeline@mantlebio.com
- We are celebrating this launch with a Computation & Biology happy hour at our SF office on August 13. Space is limited; please RSVP here.
- Learn with us!
- Share this post!
- If you enjoyed reading this, your friends might too 😀
Thank you!