Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.csbj.2020.12.021
Title: Experimental and bioinformatics considerations in cancer application of single cell genomics
Authors: Tan, Joanna Hui Juan
Kong, S.L.
Tai, Joyce A.
Poh, Huay Mei
Yao, Fei
Sia, Yee Yen
Lim, Edwin Kok Hao
Takano, Angela Maria
Tan, Daniel Shao-Weng
Javed, Asif
Hillmer, Axel M.
Keywords: Protocol aware bioinformatics
Single cell genomics
Single cell somatic variant caller
Whole genome amplification
Issue Date: 1-Jan-2021
Publisher: Elsevier B.V.
Citation: Tan, Joanna Hui Juan, Kong, S.L., Tai, Joyce A., Poh, Huay Mei, Yao, Fei, Sia, Yee Yen, Lim, Edwin Kok Hao, Takano, Angela Maria, Tan, Daniel Shao-Weng, Javed, Asif, Hillmer, Axel M. (2021-01-01). Experimental and bioinformatics considerations in cancer application of single cell genomics. Computational and Structural Biotechnology Journal 19 : 343-354. ScholarBank@NUS Repository. https://doi.org/10.1016/j.csbj.2020.12.021
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Abstract: Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient's tumour at the intercellular level. However, the DNA yield per cell is insufficient for today's sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach. © 2020 The Authors
Source Title: Computational and Structural Biotechnology Journal
URI: https://scholarbank.nus.edu.sg/handle/10635/232663
ISSN: 2001-0370
DOI: 10.1016/j.csbj.2020.12.021
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
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