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FASTGenomics blog

News from the FASTGenomics Team


In this blog, you find the latest advancemenets and features that we built into the FASTGenomics platform as well as news for the FASTGenomics community. We will also feature some news on single cell RNA-seq research that we find is related to our project: Either because it is a new workflow we would like to implement on FASTGenomics or just because we find it fascinating and think you should know about it.


Relaunch of the FASTGenomics platform

May 2019

End of May, our team got together for some big work on the platform. We completely redesigned the look and feel of the platform. This is an ongoing process and we will keep you updated on the developments. You will see some major changes happening in the next weeks and we would love to hear how you like it. Please send us your comments and suggestions to contact@fastgenomics.org.

Currently we focus on a new standard workflow that can be applied to a large collection of new data sets. The aim is to provide a reusable workflow that allows to quantitatively compare different data sets. Of course, to analyze these data further, you can still customize your own workflows and dig deeper.

The new standard workflow is written in R-markdown script, as this is common practice for many researchers in the community. Using R-markdown, we generated an interactive results notebook that allows you to easily browse the results while you can still access the underlying code. The workflow is based on the Seurat PBMC3k tutorial and has been enhanced with more features by our partners at the Schultze lab at LIMES in Bonn, Germany. We hope you find it as helpful as we did!


Science breakthrough of the year 2018: Development cell by cell

December 2018

Science journal has announced single cell RNA-seq analyses as the 2018 Breakthrough of the Year! The development cell by cell is basically a pseudo-time analysis of embryonic cells. From sciencemag.org:

“Using a variety of sophisticated computational methods, [researchers] linked single-cell RNA-seq readouts taken at different time points to reveal the turning on and off of sets of genes that defined the types of cells formed in those more complex organisms. One study uncovered how a fertilized zebrafish egg gives rise to 25 cell types; another monitored frog development through early stages of organ formation and determined that some cells begin to specialize earlier than previously thought. ‘The techniques have answered fundamental questions regarding embryology,’ says Harvard University stem cell biologist Leonard Zon.”

We at FASTGenomics are very happy to work in such a fast-developing and promising area of research and we aim to make these methods and analyses available to a broad range of researchers.


Try the new release – analyze your own data

April 2018

We are happy to announce that FASTGenomics has just been updated with a new set of features! Apart from several backend modifications, we improved some of the visualizations on the platform – you can now adapt the point size in the scatter plot on the cluster inference screen, and heatmaps now show a dendrogram both on the cluster- and the gene-axis to indicate correlation patterns.

But most of all, you can now analyze your own data with FASTGenomics.After login, use the Upload button on the project selection page to get to the upload portal. There you can provide your own gene expression table in a simple numeric text file (we provide an example table) of a size of up to 1000 megabytes, and upload it to the platform for analysis. Try it out now!

We received several inquiries regarding the privacy of your data after the upload. So here is the fine print: analysis is completely free, and your data will be kept private and will only be available to your user account – no other user can access your data set. We are working on a feature that allows you to make a data set public in case you wish to do so at a later stage. Apart from running the algorithms required to create the results for your analysis, no data mining will be performed on your data. At no point will any member of FASTGenomics use your private data sets for any commercial purposes, own publications or own research.

However: please note that, right now, we require a manual inspection by a FASTGenomics data analyst (an employee of Comma Soft) before starting the computation after data upload. Please also understand that this might cause a certain delay outside of working hours. This is done to check that the data set meets all parameter requirements of the analysis pipeline and to avoid overloading our current computational resources. The inspection only checks basic properties like size of the data set and use of the correct gene identifiers. We are currently redesigning the way we use our hardware infrastructure and hope to provide a fully automated pipeline with one of the next releases. Should you have any questions regarding the privacy of your data or should you require additional security features, please do not hesitate to get in touch!


FASTGenomics at CeBIT

March 2017

From Mar 20 to 24, the FASTGenomics team will present the first prototype at the largest German conference for digital business, the CeBIT. There we will present our solution for subtype discovery in single cell sequencing transcriptomics data. Visit us in hall 6 at the Smart Data booth of the Federal Ministry for Economic Affairs and Energy!

Now Online: Full Single Cell Subtype Analysis Workflow!

February 2017

Today we published our first release of the FASTGenomics platform. You can now access our first prototype at https://fastgenomics.org. Choose one of eight recent data sets to explore the functionality. Right now, the prototype offers you a full pipeline for subtype discovery in single cell transcriptomics data.

  • Among others, you will find tools for
  • an interactive data quality assurance screen, including a simple tool for batch effect analysis
  • t-SNE-embedding powered by deep neural networks
  • clustering with HDBSCAN
  • 3D-exploration of t-SNE-embedding for insights into clustering confidence
  • differential gene expression with generalized linear models
  • gene set enrichment analysis using GO
  • comprehensive scientific summary of all methods and results

FASTGenomics is available as a free online tool now. Try it out now!

FASTGenomics at Molecular Med Tri-Con 2017

February 2017

From February 19 to 24, FASTGenomics will be at the Molecular Medicine Tri-Conference (Molecular Med Tri-Con) in San Francisco. The Molecular Med Tri-Con concentrates on molecular medicine with special focus on the research areas of genomics, diagnostics and information technology. With over 500 international speakers from all fields of industry and research, it is one of the largest global conference in this domain. The conference features 14 tracks with more than 400 presentations and panel discussions. We will present the current state of our prototype on two posters, and our colleague Kathrin will share insights on best practices in single cell analytics. Meet her at the poster sessions in the tracks for “Bioinformatics for Big Data” and “NGS Diagnostics: Knowledge Bases, Annotation and Interpretation”.

Edit: missed the poster session? Get in touch if you have any questions or want a copy of the posters!

FASTGenomics launched!

September 2016

With a kickoff event of all involved researchers, developers and data scientists, we are happy to announce that FASTGenomics has started. FASTGenomics is a research and development project that wants to speed up a currently ongoing exciting development in genomics. Funded by the German Federal Ministry of Economy and Energy, we want to build a platform that supports researchers in the new and rapidly growing field of single cell genomics.

For some years now, next generation sequencing made it possible to run affordable genome analyses at large scales. However, transcriptome analysis was performed on the aggregated measurements of hundreds or thousands of cells. Recent advancements in sequencing technologies now make it possible to study biological processes at the fundamental level of life: the individual cell.
We are convinced that single cell sequencing will have a huge impact in medicine and microbiology, in particular in human immunology, leading to new therapies in many common diseases.

However, scientists are still struggling with challenges provided by the data. Data sets are very large, sparse, noisy, and have to be connected with many external knowledge sources to provide meaningful interpretation. FASTGenomics is addressing these challenges: together, Comma Soft AG and LIMES Institute of Bonn University want to build a platform that brings together all players in this interdisciplinary field. Comma Soft brings in over 20 years of experience in building software for knowledge management and visual analytics, while experts at LIMES provide the project with their expertise in single cell transcriptomics.
The FASTGenomics core team is currently defining a first prototype to get the most basic functionality out to users as soon as possible.