Transmorph: a unifying computational framework for modular single-cell RNA-seq data integration.

Data integration of single-cell RNA-seq (scRNA-seq) data describes the task of embedding datasets gathered from different sources or experiments into a common representation so that cells with similar types or states are embedded close to one another independently from their dataset of origin. Data integration is a crucial step in most scRNA-seq data analysis pipelines involving multiple batches. It improves data visualization, batch effect reduction, clustering, label transfer, and cell type inference. Many data integration tools have been proposed during the last decade, but a surge in the number of these methods has made it difficult to pick one for a given use case. Furthermore, these tools are provided as rigid pieces of software, making it hard to adapt them to various specific scenarios. In order to address both of these issues at once, we introduce the transmorph framework. It allows the user to engineer powerful data integration pipelines and is supported by a rich software ecosystem. We demonstrate transmorph usefulness by solving a variety of practical challenges on scRNA-seq datasets including joint datasets embedding, gene space integration, and transfer of cycle phase annotations. transmorph is provided as an open source python package.

Clonal evolution during metastatic spread in high-risk neuroblastoma.

Patients with high-risk neuroblastoma generally present with widely metastatic disease and often relapse despite intensive therapy. As most studies to date focused on diagnosis-relapse pairs, our understanding of the genetic and clonal dynamics of metastatic spread and disease progression remain limited. Here, using genomic profiling of 470 sequential and spatially separated samples from 283 patients, we characterize subtype-specific genetic evolutionary trajectories from diagnosis through progression and end-stage metastatic disease. Clonal tracing timed disease initiation to embryogenesis. Continuous acquisition of structural variants at disease-defining loci (MYCN, TERT, MDM2-CDK4) followed by convergent evolution of mutations targeting shared pathways emerged as the predominant feature of progression. At diagnosis metastatic clones were already established at distant sites where they could stay dormant, only to cause relapses years later and spread via metastasis-to-metastasis and polyclonal seeding after therapy.