Digital RNA sequencing using unique molecular identifiers enables ultrasensitive RNA mutation analysis
Understanding genetic mutations is crucial for various applications, from diagnosing diseases to unraveling the complexities of gene expression. While most mutation analysis is traditionally performed...
scSNV-seq – high-throughput phenotyping of single nucleotide variants by coupled single-cell genotyping and transcriptomics
CRISPR screens with single-cell transcriptomic readouts are a valuable tool to understand the effect of genetic perturbations including single nucleotide variants (SNVs) associated with diseases...
Novel algorithm able to detect mutations in single-cell sequencing data sets
Being able to characterise somatic mutations at single-cell resolution is essential for understanding cancer evolution and development. Until now, detecting mutations in single cells remained technically challenging. EMBL-EBI has now developed...
SUsPECT – a pipeline for variant effect prediction based on custom long-read transcriptomes for improved clinical variant annotation
Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular if they affect transcripts...
Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data
Long-read RNA sequencing (lrRNA-seq) produces detailed information about full-length transcripts, including novel and sample-specific isoforms. Furthermore, there is an opportunity to call variants directly...
scAllele – A versatile tool for the detection and analysis of variants in scRNA-seq
Single-cell RNA sequencing (scRNA-seq) data contain rich information at the gene, transcript, and nucleotide levels. Most analyses of scRNA-seq...
Detecting somatic mutations from RNA sequencing data without a matched-normal sample
Detection of somatic point mutations using patients sequencing data has many clinical applications, including the identification of cancer driver genes...
Finding a suitable library size to call variants in RNA-Seq
RNA sequencing allows the study of both gene expression changes and transcribed mutations, providing a highly effective way to gain insight into cancer biology. When planning the sequencing of...
New analytical model detects breast cancer mutations in RNA-Seq data
We hope that SCAN-B RNA sequencing will be in clinical use as early as next year, mainly to help in the identification of which breast tumours are...
AssociVar – detecting mutations based on associations from direct RNA sequencing data
One of the key challenges in the field of genetics is the inference of haplotypes from next generation sequencing data. The MinION Oxford Nanopore...
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