Sparse2big meeting in Bonn
EpiScanpy: integrated single-cell epigenomic analysis
Epigenetic single-cell measurements reveal a layer of regulatory information not accessible to single-cell transcriptomics. epiScanpy, is a computational framework for the analysis of single-cell DNA methylation and single-cell ATAC-seq data. We introduce and compare multiple feature space constructions for epigenetic data and show the feasibility of common clustering, dimension reduction and trajectory learning techniques. We find that differentially methylated and differentially open markers between cell clusters enrich transcriptome-based cell type labels by orthogonal epigenetic information.
For more information, see the preprint: Danese et al. EpiScanpy: integrated single-cell epigenomic analysis. bioRxiv, 2019. doi:10.1101/648097
Memory-driven computing accelerates genomic data processing
Next generation sequencing (NGS) is the driving force behind precision medicine and is revolutionizing most, if not all, areas of the life sciences. We provide evidence that memory-driven computing (MDC), a novel memory-centric hardware architecture, is an attractive alternative to current processor-centric compute infrastructures. USing MDC, pseudoalignment by near-optimal probabilistic RNA-seq quantification (kallisto) was accelerated by more than two orders of magnitude with identical accuracy and indicated 66% reduced energy consumption. One billion RNA-seq reads were processed in just 92 seconds. We further envision that other data-rich areas will similarly benefit from this new memory-centric compute architecture.
For more information, see the preprint: Becker et al. Memory-driven computing accelerates genomic data processing. bioRxiv, 2019. doi:10.1101/519579
Sparse2big meeting in Munich
We will meet on Monday, March 25, 2019 to discuss recent events and progress in our sparse2big project. After the event everyone is invited to join the SCOG meeting.
FASTGenomics: Platform for single-cell RNA sequencing data
FASTGenomics is a platform for single cell transcriptomics to analyze single cell expression data. Researchers from biology, medicine, and computational biology can use FASTGenomics to use the latest algorithms together with big data storage solutions and carry comfortably out their own studies. The platform is intuitive to use, meets high data protection standards, and promotes exchange and re-use in the scientific community.
For more information, see the preprint: Scholz C.J. et al. FASTGenomics: An analytical ecosystem for single-cell RNA sequencing data. bioRxiv, 2018. doi:10.1101/272476
Sparse2big kick-off meeting
The kick-off meeting for our new sparse2big consortium took place at the Helmholtz Center Munich. Sparse2big focuses on method development to deal with sparse data, in particular in single cell genomics data. Eight Helmholtz Centers work together: Joachim Schultze, Uwe Ohler, ... and collaborate with industry: Comma Soft AG, IBM, ... .