scMultiSim: simulation of single cell multi-omics and spatial data guided by gene regulatory networks and cell-cell interactions.

Simulated single-cell data is essential for designing and evaluating computational methods in the absence of experimental ground truth. Existing simulators typically focus on modeling one or two specific biological factors or mechanisms that affect the output data, which limits their capacity to simulate the complexity and multi-modality in real data. Here, we present scMultiSim, an in silico simulator that generates multi-modal single-cell data, including gene expression, chromatin accessibility, RNA velocity, and spatial cell locations while accounting for the relationships between modalities. scMultiSim jointly models various biological factors that affect the output data, including cell identity, within-cell gene regulatory networks (GRNs), cell-cell interactions (CCIs), and chromatin accessibility, hile also incorporating technical noises. Moreover, it allows users to adjust each factor's effect easily. We validated scMultiSim's simulated biological effects and demonstrated its applications by benchmarking a wide range of computational tasks, including multi-modal and multi-batch data integration, RNA velocity estimation, GRN inference and CCI inference using spatially resolved gene expression data, many of them were not benchmarked before due to the lack of proper tools. Compared to existing simulators, scMultiSim can benchmark a much broader range of existing computational problems and even new potential tasks.

scMultiSim: simulation of multi-modality single cell data guided by cell-cell interactions and gene regulatory networks.

Simulated single-cell data is essential for designing and evaluating computational methods in the absence of experimental ground truth. Existing simulators typically focus on modeling one or two specific biological factors or mechanisms that affect the output data, which limits their capacity to simulate the complexity and multi-modality in real data. Here, we present scMultiSim, an in silico simulator that generates multi-modal single-cell data, including gene expression, chromatin accessibility, RNA velocity, and spatial cell locations while accounting for the relationships between modalities. scMultiSim jointly models various biological factors that affect the output data, including cell identity, within-cell gene regulatory networks (GRNs), cell-cell interactions (CCIs), and chromatin accessibility, while also incorporating technical noises. Moreover, it allows users to adjust each factor's effect easily. We validated scMultiSim's simulated biological effects and demonstrated its applications by benchmarking a wide range of computational tasks, including cell clustering and trajectory inference, multi-modal and multi-batch data integration, RNA velocity estimation, GRN inference and CCI inference using spatially resolved gene expression data. Compared to existing simulators, scMultiSim can benchmark a much broader range of existing computational problems and even new potential tasks.

D. H. Lawrence and Sexuality: Reassessing the Novels.

As a writer of fiction, D. H. Lawrence spent his career maneuvering between heterosexual and homosexual preferences. In order to make a living, he needed to use mainstream publishers. They encouraged his bold work but only if he censored it. What especially interested Lawrence were the differences between male and female orgasm-not just the mechanics but their meaning. Over his career (1910-1930) his views on orgasm evolved from simple release, to ambivalent forms of lust, to a challenging separation of responses: unfathomable silence for males and articulate expression for females. The sexes are privileged differently, and the categorical separation that Lawrence discovers is a revelation. This essay analyzes five of his most famous novels, from Sons and Lovers to Lady Chatterley's Lover, and, based on revisions in his texts, reaches conclusions that differ from those most readers have held. In revising, Lawrence came to reshape his characters' responses into complex, often-coded narratives.

Laboratory-Developed Tests: A Legislative and Regulatory Review.

BACKGROUND: Twenty-five years ago, the Food and Drug Administration (FDA) asserted in a draft document that "home brew" tests-now commonly referred to as laboratory-developed tests (LDTs)-are subject to the same regulatory oversight as other in vitro diagnostics (IVDs)4. In 2010, the FDA began work on developing a proposed framework for future LDT oversight. Released in 2014, the draft guidance sparked an intense debate over potential LDT regulation. While the proposed guidance has not been implemented, many questions regarding LDT oversight remain unresolved. CONTENT: This review provides an overview of federal statutes and regulations related to IVDs and clinical laboratory operations, with a focus on those potentially applicable to LDTs and proposed regulatory efforts. Sources reviewed include the Code of Federal Regulations, the Federal Register, congressional hearings, guidance and policy documents, position statements, published literature, and websites. SUMMARY: Federal statutes regarding IVDs were passed without substantive evidence of congressional consideration toward the concept of LDTs. The FDA has clear oversight authority over IVD reagents introduced into interstate commerce. A 16-year delay in publicly asserting FDA authority over LDTs, the pursuit of a draft guidance approach toward oversight, and establishment of regulations under the Clinical Laboratory Improvement Amendments of 1988 (CLIA'88) applicable to LDTs contributed to community uncertainty toward LDT oversight. Future regulatory and/or legislative efforts may be required to resolve this uncertainty.