Similarity metrics for binary cell clustering: How close can we get to state-of-the-art ?

Analysing single-cell RNA sequencing data is becoming an increasingly tedious task as the size of data sets grows. As a proposed solution, recent discoveries suggest that these data sets can be binarized without losing much information. This in turn should allow for memory and time efficient methods of storage and computation. Numerous analyses...

Effect of Output Granularity on SARS-CoV-2 Variant Abundance Estimates using Domestic Wastewater Sequencing

Monitoring of SARS-CoV-2 variants is crucial to efforts in combating the COVID-19 pandemic. Lineage level abundance estimates for SARS-CoV-2 can be obtained from viral material present in domestic wastewater. The abundance predictions can be made at different levels of granularity-individual lineage level(high granularity) or variant level(low...

Distribution of Cultivated and Uncultivated Cyanobacteria and Chloroflexus-Like Bacteria in Hot-Spring Microbial Mats

Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration

OBJECTIVE: To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. METHODS: This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which...

CBA: Cluster-Guided Batch Alignment for Single Cell RNA-seq

The power of single-cell RNA sequencing (scRNA-seq) in detecting cell heterogeneity or developmental process is becoming more and more evident every day. The granularity of this knowledge is further propelled when combining two batches of scRNA-seq into a single large dataset. This strategy is however hampered by technical differences between...

Cell type specificity of glucocorticoid signaling in the adult mouse hippocampus

Glucocorticoid stress hormones are powerful modulators of brain function and can affect mood and cognitive processes. The hippocampus is a prominent glucocorticoid target and expresses both the glucocorticoid receptor (GR: Nr3c1) and the mineralocorticoid receptor (MR: Nr3c2). These nuclear steroid receptors act as ligand-dependent...

snRNA-seq analysis in multinucleated myogenic FSHD cells identifies heterogeneous FSHD transcriptome signatures associated with embryonic-like program activation and oxidative stress-induced apoptosis

The sporadic nature of DUX4 expression in FSHD muscle challenges comparative transcriptome analyses between FSHD and control samples. A variety of DUX4 and FSHD-associated transcriptional changes have been identified, but bulk RNA-seq strategies prohibit comprehensive analysis of their spatiotemporal relation, interdependence and role in the...

Predicting cell population-specific gene expression from genomic sequence

Most regulatory elements, especially enhancer sequences, are cell population-specific. One could even argue that a distinct set of regulatory elements is what defines a cell population. However, discovering which non-coding regions of the DNA are essential in which context, and as a result, which genes are expressed, is a difficult task. Some...

A data-driven methodology reveals novel myofiber clusters in older human muscles

Skeletal muscles control posture, mobility and strength, and influence whole-body metabolism. Muscles are built of different types of myofibers, each having specific metabolic, molecular, and contractile properties. Fiber classification is, therefore, regarded the key for understanding muscle biology, (patho-) physiology. The expression of...

OX40 agonism enhances PD-L1 checkpoint blockade by shifting the cytotoxic T cell differentiation spectrum

Immune checkpoint therapy (ICT) has the power to eradicate cancer, but the mechanisms that determine effective therapy-induced immune responses are not fully understood. Here, using high-dimensional single-cell profiling, we interrogate whether the landscape of T cell states in the peripheral blood predict responses to combinatorial targeting...

Collective migration and phenotypic plasticity in cancer metastasis: Conflicting views or complementary mechanisms?

Cancer metastasis, the spread of cancer to distant organs, is the major cause of cancerrelated mortality. Hence, understanding the mechanisms underlying cancer metastasis is crucial to improve clinical interventions. Despite intensive efforts, the driving mechanisms remain ill-understood due to the difficulties posed by studying the different...

Predicting immune responses on multi-modal single-cell data with variational inference

Single-cell sequencing allows measuring individual cells' molecular features and their responses to perturbations. Understanding which cells respond to a particular perturbation and how these responses vary across populations can be used to, for example, improve vaccine immunogenicity. However, an exhaustive exploration of single-cell...

Improving cell type matching across species in scRNA-seq data using protein embeddings and transfer learning

Knowing the relation between cell types is crucial for translating experimental results from mice to humans. Establishing cell type matches, however, is hindered by the biological differences between the species. A substantial amount of evolutionary information between genes that could be used to align the species, is discarded by most of the...

The eQTL and beyond: a cell type specific view on genetic variant-associated changes in gene (co-)expression in the context of Alzheimer’s Disease

Understanding the role of genes and genetic variants is a key challenge in unraveling the driving mechanisms of Alzheimer's disease (AD). Single-cell RNA sequencing is a technique that quantifies gene expression at the cell (type) level enabling investigation of the roles of different cell types in disease. We analyzed changes in gene (co-...