Patrik L. Ståhl

Spatially resolved integrative analysis of transcriptomic and metabolomic changes in tissue injury studies

The paper introduces MAGPIE, a framework for integrating spatial transcriptomics, metabolomics, and tissue morphology data, demonstrating its application in studying drug-induced pulmonary fibrosis.

Spatio-Temporal Multi-Omics Profiling of Mechanisms and Biomarkers in Inhaled Drug-Induced Lung Toxicity

This study develops a multi-omics framework to identify biomarkers of inhaled drug-induced lung toxicity using spatial transcriptomics, proteomics, and histopathological data.

Hidden network preserved in Slide-tags data allows reference-free spatial reconstruction

The paper reanalyzes Slide-tags data to reveal a latent spatial network enabling reference-free tissue reconstruction.

Translational mapping of spatially resolved transcriptomes in human and mouse pulmonary fibrosis

This study maps spatial transcriptomes of human and mouse pulmonary fibrosis to identify fibrotic niches and differences in alveolar regeneration.

Lokatt: A hybrid DNA nanopore basecaller with an explicit duration hidden Markov model and a residual LSTM network

Lokatt improves nanopore basecalling by combining an explicit duration HMM with a residual LSTM, achieving high accuracy and coverage on E. coli data.

Chromatin accessibility profiling in tissue sections by spatial ATAC

This paper introduces spatial ATAC, a method for spatially resolved chromatin accessibility profiling, and demonstrates its application in studying gene regulation in mouse development and human disease.

Three-dimensional spatial transcriptomics uncovers cell type dynamics in the rheumatoid arthritis synovium

This study uses spatial transcriptomics to analyze cell type dynamics in rheumatoid arthritis synovium, revealing chemokine-driven interactions in inflamed tissue.

High-density spatial transcriptomics arrays for in situ tissue profiling

This paper introduces HDST, a high-resolution spatial transcriptomics method, and demonstrates its application in mouse brain tissue to resolve spatial expression patterns and cell types.

Conbase: a software for unsupervised discovery of clonal somatic mutations in single cells through read phasing

Conbase identifies clonal somatic mutations in single cells using read phasing, validated on simulated data and human samples.

Multidimensional transcriptomics provides detailed information about immune cell distribution and identity in HER2+ breast tumors

This study uses multidimensional transcriptomics to analyze immune cell distribution and identity in HER2+ breast tumors, revealing spatial heterogeneity and interpatient differences in immune infiltration.