Resource Centre
Workflow 
Workflow overview: single-cell transcriptomics
Workflow 
Workflow overview: direct RNA sequencing
Publication 
Using deep long-read RNAseq in Alzheimer’s disease brain to assess clinical relevance of RNA isoform diversity
Poster 
Unlocking Nanopore sequencing for managing food safety in the food industry
Publication 
Transcriptome variation in human tissues revealed by long-read sequencing
Poster 
Transcriptome profiling of Korean colon cancer by cDNA PCR Nanopore sequencing
Poster 
Transcriptome analysis using long nanopore reads
Publication 
Transcriptional readthrough precedes alternative splicing programs triggered in CML cells by imatinib
Publication The costimulatory domain influences CD19 CAR-T cell resistance development in B-cell malignancies
Publication 
TEQUILA-seq: a versatile and low-cost method for targeted long-read RNA sequencing
Publication 
Targeting sex determination to suppress mosquito populations
Publication 
Targeted long-read sequencing enriches disease-relevant genomic regions of interest to provide complete Mendelian disease diagnostics
Publication 
Targeted long-read sequencing as a single assay improves diagnosis of spastic-ataxia disorders
Publication 
Systematic characterisation of full-length RNA isoforms in human colorectal cancer at single-cell resolution
Publication 
A systematic benchmark of nanopore long-read RNA sequencing for transcript-level analysis in human cell lines
Poster 
Successful training of laboratories in Asia and Africa to use nanopore sequencing for poliovirus surveillance
Poster 
Study of SPG11’s splicing, in neuronal and non-neuronal cells, by long-read sequencing: implication on phenotype
Publication 
Single-cell rapid capture hybridization sequencing (scRaCH-seq) to reliably detect isoform usage and coding mutations in targeted genes at a single-cell level
Publication 
Single-cell multiomics reveal the scale of multi-layered adaptations enabling CLL relapse during venetoclax therapy
Publication Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer
