Project R-11906

High Dimensional Clustering and prediction and integrated analysis of single Cell RNAseq Data (Research)

The single cell RNA-sequencing technology allows the assessment of heterogenous cell-specific changes and their biological characteristics. In the project, we focus on a single cell multi-omics data for immune profiling purposes. T-cells exhibit unique behavior referred to as cross-reactivity; the ability of T-Cells to recognize two or more peptide MHC complexes by the TCR. A CD8+ T Cell is defined as specific for an antigen if the cell binds to the antigen. Our work is applied on single cell RNA-seq data(publicly available in https://support.10xgenomics.com/single-cell-vdj/datasets/) consisting of CD8+ T Cells obtained using a state of the art single cell multi-omics technology from 10X Genomics and our aim is to assess and understand the heterogeneic characteristics and the binding specificities of these CD8+ T Cells, i.e., we aim to identify the specificity of the CD8+ T cells to one (or more) antigen(s). For the identification of specific CD8+ T Cells, we focus on both unsupervised and supervised data analysis pipeline. Biclustering and clustering methods are applied to recover and explore the cross reactive behaviour of T Cells and to identify a subset of cells which are specific to a subset of antigens. Clustering methods are used to link these subsets to the RNA-seq data.

16 September 2020 - 31 July 2026