Fabian J. Theis

SCANPY: large-scale single-cell gene expression data analysis

Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inferenc...

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

Diffusion pseudotime robustly reconstructs lineage branching

The temporal order of differentiating cells is intrinsically encoded in their single-cell expression profiles. We describe an efficient way to robustly estimate this order accor...

Diffusion maps for high-dimensional single-cell analysis of differentiation data

Abstract Motivation: Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in...

<i>destiny</i> : diffusion maps for large-scale single-cell data in R

Abstract Summary: Diffusion maps are a spectral method for non-linear dimension reduction and have recently been adapted for the visualization of single-cell expression data. He...

Reconstructing cell cycle and disease progression using deep learning

We show that deep convolutional neural networks combined with nonlinear dimension reduction enable reconstructing biological processes based on raw image data. We demonstrate th...

Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling

BackgroundThe understanding of regulatory and signaling networks has long been a core objective in Systems Biology. Knowledge about these networks is mainly of qualitative natur...

Single cells make big data: New challenges and opportunities in transcriptomics

Recent technological advances have enabled unprecedented insight into transcriptomics at the level of single cells. Single cell transcriptomics enables the measurement of tran- ...