A single-cell quality-control portal for collection, sharing and analysis of single-cell experiment QC data.
Single-cell sequencing is becoming a commonly used tool by biologists. Systems like 10XGenomics, Fluidigm’s C1, Drop-Seq or SeqWell are making the generation of single-cell RNA-Seq data relatively simple; however there is a high degree of variability on the success of single-cell projects.
This portal aims to make it easier for users to share their experiences via upload of experimental metadata* and platform specific QC reports*. Users can also filter and query the database for experimental factors e.g. specific sample types, dissociation protocol, etc, and identify which protocol modifications may be best applied to their own experiments.
This site provides an easy to use web interface for the collection, processing and analysis of MIAME1 style experimental meta-data and single-cell QC reports, e.g. 10X Genomics Cell Ranger®. By providing the single-cell community this central portal for comparison of these data SCQC will enable more rapid identification of the factors that may be beneficial, or detrimental, to single-cell analysis. As well as helping with the development of best practices and standards by allowing users to more quickly assemble meta-analysis of different datasets. It will also help by connecting users in the single-cell community.
SQCQ uses a basic MIASCE: Minimal Information About a Single-Cell Experiment, for collection of experimental meta-data for comparison and sharing of results between collaborating and disparate laboratories alike. Users submit metadata when submitting their QC reports – a batch upload tool is in development.
We hope that SCQC will enable more rapid identification of the factors that may be beneficial, or detrimental, to single-cell sequencing experiments. And will help with speed the development of best practices and standards in the field.
All data submitted should be anonymised and will be available for download for local analysis by registered users. Additionally SCQC portal code and software used is available on GitHub under the MIT open-source license.
We have applied for funding to extend the SCQC QC portal to other single-cell technologies (currently only 10X Genomics is supported), and develop the site to accommodate future technologies, which will enable in-depth cross-platform QC analyses to be performed. Making data available for more than scRNA-Seq requires consideration of the best QC metrics to include from technologies as diverse as in-situ hybridization or other high-content imaging platforms, proteomics, metabolomics, and epigenetics. We will engage with the community around these QC standards as they develop. However the SCQC portal will collect similar metadata from users of these different technologies simplifying comparison of multiple approaches to tissue preparation and sample handling. Ultimately the community will need to know if the same methods can be used across different technologies or whether tissues and cells need to be handled very differently to generate the very best results.
The development plan includes: