Computational Immunology

PI/Head: Mai Chan Lau, Ph.D. (Joint Appointee)
Email: Lau_Mai_Chan@bii.a-star.edu.sg

The Computational Immunology Platform uses state-of-the-art methods to analyse scientific data and deliver pipelines and workflows to accelerate research.

Overview

The Computational Immunology platform supports various types of data analytics including exploratory, hypothesis-driven, descriptive, and predictive analytics. The team uses state-of-the-art methods to analyse scientific data from SIgN and other A*STAR research entities, hospitals, universities, and companies, and delivers pipelines and workflows to accelerate research. The Computational Immunology team handles diverse types of immunological data including next-generation sequencing (NGS) data, flow cytometry, ELISA, Quanterix and Luminex assays, tissue-based molecular imaging data, spatial transcriptomics, and assesses the cross-correlation between them.

Focus Areas

  • NGS (ISO-certified RNA-Seq workflow) and NanoString targeted assay analysis (Figure 1)
  • Microbiome analysis (metagenomics and 16s RNA) (Figure 2)
  • Spatial transcriptomics analysis (10x Visium, NanoString GeoMx) (Figure 3)
  • Tissue-based molecular image analysis (IMC data) (Figure 4)
  • Integrative analysis (Figure 5)

Figure 1: RNAseq analysis of COVID-19 patients and healthy controls (HCs) using (a) principal component analysis,  (b)  heatmap, (c) top canonical pathways and upstream regulators associated with the DEGs (Ingenuity Pathway Analysis), and (d) integrated network analysis.(1)


Figure 2: Microbiome analysis of skin metagenomics  data using Bray-Curtis dissimilarity (at species-level) visualized in PCoA plot (left) and box plots (right).(2)


Figure 3: Spatial transcriptomics analysis on SARS-CoV-2 infected tumor samples using Visium (10× Genomics).(3)


Figure 4: Image processing and downstream cell phenotyping analysis using imaging mass cytometry data.


Figure 5: A graph-based network analysis of the interaction between cytokine level and immune cellular frequencies in COVID-19 patients. Association is shown with regard to the timing (left) and the severity (right).(4)

Key Applications & Tools Used

  • QIAGEN Ingenuity Pathway Analysis (IPA)
  • Tibco Spotfire
  • StockinLab (LIMS)
  • Blood Requisition System
  • R
  • MySQL

Computing / Data Resources

  • Multiple Computational Servers for Data Analysis (96+ Core CPU, 1+TB RAM, GPU, etc.)
  • Cumulative Storage of about 1PB (1000TB)

References

  1. Fong SW, Yeo NK, Chan YH, Goh YS, Amrun SN, Ang N, Rajapakse MP, Lum J, Foo S, Lee CY, Carissimo G, Chee RS, Torres-Ruesta A, Tay MZ, Chang ZW, Poh CM, Young BE, Tambyah PA, Kalimuddin S, Leo YS, Lye DC, Lee B, Biswas S, Howland SW, Renia L, Ng LFP. Robust Virus-Specific Adaptive Immunity in COVID-19 Patients with SARS-CoV-2 Δ382 Variant Infection. J Clin Immunol. 2022 Feb;42(2):214-229. doi: 10.1007/s10875-021-01142-z. Epub 2021 Oct 30. Erratum in: J Clin Immunol. 2021 Nov 27;: PMID: 34716845; PMCID: PMC8556776.

  2. Tham KC, Lefferdink R, Duan K, Lim SS, Wong XFCC, Ibler E, Wu B, Abu-Zayed H, Rangel SM, Del Duca E, Chowdhury M, Chima M, Kim HJ, Lee B, Guttman-Yassky E, Paller AS, Common JEA. Distinct skin microbiome community structures in congenital ichthyosis. Br J Dermatol. 2022 Oct;187(4):557-570. doi: 10.1111/bjd.21687. Epub 2022 Jul 4. PMID: 35633118; PMCID: PMC10234690

  3. Lau MC, Yi Y, Goh D, Cheung CCL, Tan B, Lim JCT, Joseph CR, Wee F, Lee JN, Lim X, Lim CJ, Leow WQ, Lee JY, Ng CCY, Bashiri H, Cheow PC, Chan CY, Koh YX, Tan TT, Kalimuddin S, Tai WMD, Ng JL, Low JG, Lim TKH, Liu J, Yeong JPS. Case report: Understanding the impact of persistent tissue-localization of SARS-CoV-2 on immune response activity via spatial transcriptomic analysis of two cancer patients with COVID-19 co-morbidity. Front Immunol. 2022 Sep 12;13:978760. doi: 10.3389/fimmu.2022.978760. PMID: 36172383; PMCID: PMC9510984.

  4. Lim J, Puan KJ, Wang LW, Teng KWW, Loh CY, Tan KP, Carissimo G, Chan YH, Poh CM, Lee CY, Fong SW, Yeo NK, Chee RS, Amrun SN, Chang ZW, Tay MZ, Torres-Ruesta A, Leo Fernandez N, How W, Andiappan AK, Lee W, Duan K, Tan SY, Yan G, Kalimuddin S, Lye DC, Leo YS, Ong SWX, Young BE, Renia L, Ng LFP, Lee B, Rötzschke O. Data-Driven Analysis of COVID-19 Reveals Persistent Immune Abnormalities in Convalescent Severe Individuals. Front Immunol. 2021 Nov 19;12:710217. doi: 10.3389/fimmu.2021.710217. PMID: 34867943; PMCID: PMC8640498.