Fastgenomics

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COMPLEX ANALYSES

MADE EASY

FEATURES AND FUNCTIONALITY OF THE PLATFORM

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.

Therefore, we have developed FASTGenomics. Here, you can analyze public and private datasets and you can choose between several best practices workflows and browse existing analyses. FASTGenomics thus provides reproducibility even to complex analyses with large datasets.

what FASTGenomics offers

  • Intuitive analysis environment with cloud access from everywhere
  • Support of multiple data formats (mtx, rds, hdf5, h5ad, loom, csv, tsv)
  • R and Python: use Seurat and ScanPy with full support of their associated data objects
  • Data management: share your data and metadata with colleagues, coworkers or publish
  • State-of-the-art analytics: constantly growing number of analyses from renowned working groups
  • Interactive analyses using Jupyter notebooks
  • Showcase of results: make your analysis available to the community
  • Reproducibility and reusability of your results through dockerized environments

DATA MANAGEMENT

Share your own data sets with meta data and full documentation with colleagues. FASTGenomics provides you with templates for sharing contracts and a secure cloud infra-structure.

ANALYSIS & EXPLORATION

Start batch analyses in the cloud or interactively explore your data sets with best-practices analytical workflows. Alternatively, write your own analysis pipeline and share it with others.

PUBLICATION

Showcase your results to your colleagues and let them test it interactively. Use our AI-based methods and visualizations to capture your target audience with detailed insights to your research.

JUPYTER NOTEBOOKS

Jupyter notebooks have emerged as a versatile tool for explorative data analysis. Working in a notebook is as easy as coding can be. Our notebooks are built on top of highly effective images available in both Python and R. Best-practives notebooks are made available with ample documentation and interpretation of example results to get you started. Notebooks can also be easily exported for presentation purposes, making them an ideal tool to share results.

VISUAL DATA
EXPLORATION

By using some of the largest existing publicly available scRNA-seq vdatasets, 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-theart
algorithms.

GITHUB ACCESS

FASTGenomics already comes with a large variety of available tools and methods. However, you can also access code from your own repository within our platform. Just clone or install your Github repository on top of our images and get started: test your methods on a large amount on public data sets, compare your algorithm to best-practices analyses, and validate the results of your own pipeline against published findings.

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.

AI-BASED METHODS

Single-cell data sets are typically very large, noisy and highly interconnected with other annotation data, making them unsuitable for established procedures. This setting calls for the application of novel algorithms originating from the field of artificial intelligence, which are adapted to deal with this type of challenge. FASTGenomics provides AI-based methods for several applications including dimensional reduction, clustering, pattern recognition and cell typing.

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.