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Activity Number: 442 - Methods for Single-Cell and Microbiome Sequencing Data
Type: Topic Contributed
Date/Time: Thursday, August 6, 2020 : 10:00 AM to 11:50 AM
Sponsor: Biometrics Section
Abstract #309712
Title: Statistical Analysis of Coupled Single-Cell RNA-Seq and Immune Profiling Data
Author(s): Hongkai Ji* and Zhicheng Ji
Companies: Johns Hopkins Univ, Bloomberg School of Public Health and Johns Hopkins Bloomberg School of Public Health
Keywords: single cell ; RNA-seq; cancer; immune; genomics; data integration

We present an analytical framework for analyzing coupled single-cell transcriptome (scRNA-seq) and T cell receptor sequencing (scTCR-seq) data. The framework provides key functions for preprocessing, aligning cells from different samples, detecting differential gene expression across biological conditions, analyzing sequence features in T cell repertoire, and linking sequence features to gene expression signatures. We demonstrate this framework by analyzing single-cell data both from public databases and from a neoadjuvant immunotherapy clinical trial for non-small cell lung cancer.

Authors who are presenting talks have a * after their name.

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