Data processing articles from across Nature Portfolio

This Comment outlines the creation of the Global Alliance for Spatial Technologies (GESTALT), a collaborative initiative aimed at fostering the growth and standardization of spatial tissue profiling technologies. It explores the need for GESTALT, its community-driven structure and its goals, spanning from the immediate to the long term.

Inspired by recent approaches for natural language processing and computer vision, we developed Annotatability, a framework that analyzes deep neural network training dynamics to interpret pre-annotated single-cell and spatial omics data. Annotatability identified erroneous annotations and ambiguous cell states, inferred trajectories from binary labels, and revealed underlying biological signals.

PopV is an ensemble method for cell type labeling in single-cell genomics. A Cell Ontology-inspired voting procedure across different algorithms highlights low confidence annotations, thereby guiding human-in-the loop components of the annotation process.

We discuss the thirty-year anniversary of the seminal work on DNA computing and its implications for the field of biotechnology.

We developed ehrapy, an open-source Python software framework for the exploratory analysis of electronic health record data. Ehrapy handles various widely used data formats, preprocessing tasks such as imputation of missing data and bias detection, and offers tools for analyses including patient stratification, survival analysis, causal inference and trajectory inference.