Gunn, D. A. | Search bioRxiv

bioRxiv2025

BLASE: Bulk Linkage Analysis for Single Cell Experiments - Teasing Out the Secrets of Bulk Transcriptomics with Trajectory Analysis

1MotivationscRNA-seq experiments can capture cell process trajectories. Bulk RNA-seq is more practical, however does not have the granularity to elucidate cell-type specific trajectories. Deconvolution methods can estimate cell-types in RNA-seq data, but there is a need for methods characterising their pseudotime. ResultsWe show that our method, BLASE, can identify the progress of an RNA-seq sample through a trajectory in a scRNA-seq reference. ConclusionBLASE can be used to a) annotate scRNA-seq data from existing RNA-seq, b) identify progress of RNA-seq data through a process based on scRNA-seq data, and c) be used to correct developmental differences in RNA-seq differential expression analysis.

bioinformatics↗

bioRxiv2023

SenPred: A single-cell RNA sequencing-based machine learning pipeline to classify senescent cells for the detection of an in vivo senescent cell burden

Senescence classification is an acknowledged challenge within the field, as markers are cell-type and context dependent. Currently, multiple morphological and immunofluorescence markers are required for senescent cell identification. However, emerging scRNA-seq datasets have enabled increased understanding of the heterogeneity of senescence. Here we present SenPred, a machine-learning pipeline which can identify senescence based on single-cell transcriptomics. Using scRNA-seq of both 2D and 3D deeply senescent fibroblasts, the model predicts intra-experimental and inter-experimental fibroblast senescence to a high degree of accuracy (>99% true positives). We position this as a proof-of-concept study, with the goal of building a holistic model to detect multiple senescent subtypes. Importantly, utilising scRNA-seq datasets from deeply senescent fibroblasts grown in 3D refines our ML model leading to improved detection of senescent cells in vivo. This has allowed for detection of an in vivo senescent cell burden, which could have broader implications for the treatment of age-related morbidities.

cell biology↗