A platform for a quickly growing community

Single cell RNA-sequencing (scRNA-seq) is currently the most promising approach to define cellular identity and the regulation of a cell’s molecular circuitries. Different scRNA-seq technologies have been introduced and a surprisingly large number of different computational analysis methods have already been developed. Yet, the accessibility of single cell RNA-data for re-analysis or the application of existing algorithms to new data is still a daunting task, even for the experienced computational biologist.

  • Visual data exploration

    By using some of the largest existing publicly available scRNA-seq datasets, we demonstrate how visual data exploration and biological interpretation can accelerate the use of scRNA-seq both in small but also large scale scRNA-seq projects. Our goal is to provide standard analysis workflows to domain experts, without tiresome technical adaptations, while still relying on state-of-the-art algorithms.

  • Community exchange

    Science is based on the exchange of knowledge. More than many other research domains, single cell analytics relies on the interdisciplinary exchange between experts of many different research areas. This is why each FASTGenomics analysis screen supports an open forum to allow all users to exchange ideas on what they see.

  • State of the art analytics

    Single Cell analytics is a new dynamic research field with many open questions, e.g. regarding preprocessing of data, removing technical noise, and how to best identify and visualize biological signals in the highdimensional data. The FASTGenomics team is closely following current research developments to always include the best and fastest algorithmical solutions.

  • App store

    In future extensions, we plan to provide analytical tools in a publicly available app-store. Your own analytical tools can then be easily integrated into the analytical pipelines, and standardized data processing pipelines can be pre-defined.