Fluidics based single cell RNASeq (scRNASeq) provides a high throughput method for
quantifying gene expression at single cell resolution. However, it remains unclear whether …

Single-cell technologies enable measure of unique cellular signatures, but are typically
limited to a single modality. Computational approaches allow integration of diverse single …

Accurately and reliably capturing actual biological signals from single-cell transcriptomics is
vital for achieving legitimate scientific results, which is unfortunately hindered by the …

Circulating nucleic acids in blood plasma form an attractive resource to study human health
and disease. Here, we applied mRNA capture sequencing of blood plasma cell-free RNA …

Understanding the complexity of biological systems requires a comprehensive analysis of
their cell populations. Ideally, this should be done at the single cell level, because bulk …

Single cell and spatially resolved 'omic'techniques have enabled deep characterization of
clinical pathologies that remain poorly understood, providing unprecedented insights into …

Quality control (QC) is the first critical step in single cell and spatial data analysis pipelines.
QC is particularly important when analysing data from primary human samples, since …

Liquid biopsy has emerged as a promising non-invasive approach for detecting, monitoring
diseases, and predicting their recurrence. However, the effective utilization of liquid biopsy …

Abstract Background Cell‐free long RNAs in human plasma and extracellular vesicles (EVs)
have shown promise as biomarkers in liquid biopsy, despite their fragmented nature …

Cell-free RNAs (cfRNAs) offer an opportunity to detect diseases from a transcriptomic
perspective, however, existing techniques have fallen short in generating a comprehensive …