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Title
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STEGO.R : an application to aid in scRNA-seq and scTCR-seq processing and analysis
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Author
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Abstract
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| Introduction The hypervariable T cell receptor (TCR), created through somatic recombination, allows for recognition of a diverse array of antigens. Single sequencing technologies allow capture of both the single cell expression data (scRNA-seq) with the paired single cell TCR sequencing (scTCR-seq). However, the current analytical pipelines have limited capacity to integrate both data levels. To overcome these limitations, we developed STEGO (Single cell TCR and Expression Grouped Ontologies) Shiny R application to facilitate the complex analysis required for understanding T cells role in various conditions. Program parameters STEGO.R application includes the Seurat quality control (QC) process, merging with Harmony, followed by semi-supervised cellular annotations with scGate. The scRNA-seq with scTCR-seq is broken down into four sections: top clonotype, expanded clonotypes, clustering (ClusTCR2) and target epitopes from TCRex predictions. The Shiny R interface also facilitates the program’s accessibility to novice R coders. The application can be found at https://github.com/KerryAM-R/STEGO.R. Preliminary analysis Out of 22 selected public datasets, 12 could be processed with STEGO.R. We re-interrogated the dataset concerning colon inflammations following melanoma therapies, as original studies did not integrate the scRNA-seq with scTCR-seq analysis. From one study, our novel process identified that the colitis expanded T cells were cytotoxic CD8+ T cells with over-represented transcripts including IFNG, GNLY, PFR1, GZMB, NKG7, HLA-DR, KLRD1 transcripts relative to both the non-expanded clonotypes, non-colitis cases and healthy colon donors. The analysis also identified a TRGV4 cluster associated with melanoma cases as well as two TRBV6-2 clusters specific to colitis. Discussion STEGO.R facilitates fast and reproducible analysis of complex scRNA-seq with TCR repertoire data. We have demonstrated its utility by extracting novel biologically relevant insights into T-cells. We anticipate this program will facilitate the identification of subtle T population differences and if these are specific to a TCR clone and/or the expanded repertoire. |
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Language
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English
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Publication
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bioRxiv
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2023
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DOI
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10.1101/2023.09.27.559702
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Volume/pages
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(2023)
, p. 1-24
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Full text (Publisher's DOI)
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Full text (open access)
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