Search bioRxiv⌕ Search

Biology subjects

Mullan, K. A.

Publications and source records attributed to Mullan, K. A..

2 recordsLinked to original sources

STEGO.R: an application to aid in scRNA-seq and scTCR-seq processing and analysis.

The T-cell receptor (TCR) carries critical information regarding T-cell functionality. The TCR, despite its importance, is underutilized in single cell transcriptomics, with gene expression (GEx) features solely driving current analysis strategies. Here, we argue for a switch to a TCR-first approach, which would uncover unprecedented insights into T cell and TCR repertoire mechanics. To this end, we curated a large T-cell atlas from 12 prominent human studies, containing in total 500,000 T cells spanning multiple diseases, including melanoma, head-and-neck cancer, T-cell cancer, and lung transplantation. Herein, we identified severe limitations in cell-type annotation using unsupervised approaches and propose a more robust standard using a semi-supervised method or the TCR arrangement. We then showcase the utility of a TCR-first approach through application of the novel STEGO.R tool for the successful identification of hyperexpanded clones to reveal treatment-specific changes. Additionally, a meta-analysis based on neighbor enrichment revealed previously unknown public T-cell clusters with potential antigen-specific properties as well as highlighting additional common TCR arrangements. Therefore, this paradigm shift to a TCR-first with STEGO.R highlights T-cell features often overlooked by conventional GEx-focused methods, and enabled identification of T cell features that have the potential for improvements in immunotherapy and diagnostics. One Sentence SummaryRevamping the interrogation strategies for single-cell data to be centered on T cell receptor (TCR) rather than the generic gene expression improved the capacity to find relevant disease specific TCR. Key PointsO_LIThe TCR-first approach captures dynamic T cell features, even within a clonal population. C_LIO_LIA novel [~]500,000 T-cell atlas to enhance single cell analysis, especially for restricted populations. C_LIO_LINovel STEGO.R program and pipeline allows for consistent and reproducible interrogating of scTCR-seq with GEx. C_LI

bioinformatics↗

TCR_Explore: a novel webtool for T cell receptor repertoire analysis

T cells expressing either alpha-beta or gamma-delta T cell receptors (TCR) are critical sentinels of the adaptive immune system, with receptor diversity being essential for protective immunity against a broad array of pathogens and agents. Programs available to profile TCR clonotypic signatures can be limiting for users with no coding expertise. Current analytical pipelines can be inefficient due to manual processing steps, open to data transcription errors and have multiple analytical tools with unique inputs that require coding expertise. Here we present a bespoke webtool designed for users irrespective of coding expertise, coined TCR_Explore, incorporating automated quality control steps that generates a single output file for creation of flexible and publication ready figures. TCR_Explore will elevate a users capacity to undertake in-depth TCR repertoire analysis of both new and pre-existing datasets for identification of T cell clonotypes associated with health and disease. The web application is located at https://tcr-explore.erc.monash.edu for users to interactively explore TCR repertoire datasets. Key PointsO_LIBespoke program for non-specialists in computerised methodologies for deep exploration of TCR repertoire analysis C_LIO_LIAutomated QC and analysis pipelines for Sanger based TCR sequencing coupled with immunophenotyping, with the capacity for integration of other sequencing platform outputs C_LIO_LIAutomated summary processes to aid data visualisation and generation of publication-ready graphical displays C_LI

bioinformatics↗