Saskia Freytag

SpaMTP: Integrative Statistical Analysis and Visualisation of Spatial Metabolomics and Transcriptomics data.

SpaMTP integrates spatial metabolomics and transcriptomics data through a comprehensive analysis pipeline and visualization tools.

An integrative spatial multi-omic workflow for unified analysis of tumor tissue

This paper introduces a workflow for integrating spatial transcriptomics and metabolomics data to analyze glioma tissue, identifying novel biological features at the tumor's infiltrating edge.

A new genetically engineered transplant model of glioma recapitulates key phenotypes of low- and high-grade gliomas

This paper develops genetically engineered mouse cell line models (GEM-CLeMs) of glioma that recapitulate key phenotypes of low- and high-grade gliomas, offering a more accurate model of the tumor microenvironment than existing cell lines.

Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

This paper compares patient-derived neurosphere and organoid models of glioblastoma, showing they retain intra-tumoral heterogeneity and respond to chemotherapy.

TIRE-seq: an Integrated Sample Extraction and Transcriptomics Workflow for High Throughput Perturbation Studies

TIRE-seq streamlines RNA-seq workflows by integrating mRNA purification into library preparation, improving efficiency and data quality in perturbation studies.

A Risk-reward Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq

This study evaluates sample multiplexing reagents and protocols for scRNA-Seq, finding that workflow improvements and reagent choice impact data quality and cost-effectiveness.

Matrix selection for the visualization of small molecules and lipids in brain tumors using untargeted MALDI-TOF mass spectrometry imaging

The paper compares matrix, deposition technique, and polarity settings in MALDI-TOF mass spectrometry imaging for brain tumors, finding recrystallized cyano-4-hydroxycinnamic acid in positive polarity provides best performance.

A modular dCas9-based recruitment platform for combinatorial epigenome editing

The paper introduces a modular dCas9-based platform for combinatorial epigenome editing, demonstrating its ability to control effector recruitment and spatial organization for improved transcriptional regulation.

Mouse microglia express unique miRNA-mRNA networks to facilitate age-specific functions in the developing central nervous system

This study identifies unique miRNA-mRNA networks in mouse microglia during CNS development and homeostasis, revealing their role in age-specific functions and disease states.

Whole-transcriptome RNA editing analysis in single cortical neurons links locus 15q11 with psychiatric illness

The paper identifies RNA editing sites in single cortical neurons and links locus 15q11 with psychiatric illness through differential editing in cell types.

Guiding and interpreting brain network classification with transcriptional data

This paper introduces a method to improve fMRI network classification by integrating transcriptional data, enhancing prediction accuracy for schizophrenia and enabling biological interpretation of functional connectivity features.

scRNA-seq mixology: towards better benchmarking of single cell RNA-seq analysis methods

The paper benchmarks scRNA-seq analysis methods using synthetic datasets generated from mixed cancer cell lines, identifying methods that perform well across tasks like normalization, clustering, and integration.

dtangle: accurate and fast cell-type deconvolution

dtangle deconvolves cell-type proportions from bulk RNA-seq data, showing competitiveness with existing methods and utility in analyzing immune responses to Lyme disease.

Cluster Headache: Comparing Clustering Tools for 10X Single Cell Sequencing Data

This paper compares clustering methods for 10X scRNA-seq data using human datasets, finding that clustering results vary widely and are influenced by ribosomal gene expression.