Bioinformatics facility

Welcome to the Bioinformatics Facility at Barts Cancer Institute, Queen Mary University of London. We provide data analysis and consultancy services for high-throughput measurements, including DNA and RNA sequencing, single-cell and spatial transcriptomics, epigenomics and proteomics.

Our team has extensive experience analysing large-scale omics datasets and applying a range of analytical approaches tailored to the needs of each project. We have also curated a collection of publicly available datasets that can be used to validate findings and integrate with new data.

The facility supports research projects at every stage, from advising on experimental design to contributing to manuscript and grant preparation. We also develop new analytical methods and pipelines to analyse data generated by emerging technologies, including single-cell transcriptomics, immune profiling and genome sequencing.

Getting Started

Please fill in a project request form (please link here the attached form) and contact Professor Jun Wang or Dr Eleni Maniati.

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Acknowledgements

• The Bioinformatics Facility is funded by the CRUK City of London Core Award CTRQQR-2021\100004.
• We work collaboratively and support design, analysis and interpretation of data. In accordance with authorship criteria, we require authorship to be offered to our staff who have contributed to conceptualization, experimental design, data analysis and/or interpretation when any of these has been included in related manuscripts.
• In addition, please use the following phrase to acknowledge our funding: The Bioinformatics Facility is supported by the CRUK City of London Core Award to Barts Cancer Institute (CTRQQR-2021\100004).

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Prices

Please contact  Professor Jun Wang or Eleni Maniati to discuss your project requests and costing. We will charge a collaborative service fee to cover basic computation costs and data storage. We will retain a copy of your data until publication of the study and for a short period after that.

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Next generation sequencing data analysis

• Genome Sequencing Analysis: Comprehensive analysis of Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES), SNP, and CGH arrays. We offer end-to-end analysis, from raw sequencing data to the identification of single nucleotide variants (SNVs), InDels, and copy number aberrations (CNAs).
• Transcriptome Profiling: In-depth analysis of gene expression through bulk RNA sequencing (RNA-seq) and microarrays. Our services cover everything from raw sequencing data to differential expression analysis, gene set enrichment, and visualisation of results.
• Single-Cell RNA-Seq: Advanced single-cell transcriptomics to examine gene expression at the individual cell level, enabling high-resolution insights into cellular diversity and function.
• Spatial Transcriptomics: spatial transcriptomic analysis, linking gene expression data with tissue architecture to explore spatial organisation and localisation patterns.
• Small RNA-Seq: Detailed profiling of small non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), providing insights into regulatory mechanisms.
• ChIP-Seq Analysis: Comprehensive analysis of ChIP sequencing, including quality control, peak calling, and differential binding analysis, to investigate protein-DNA interactions.

Multi-Dimensional, Multi-Source Data Analysis

• Quantitative Proteomics and Phospho-Proteomics: Analysis of differential protein abundance and phospho-proteomic profiles, coupled with pathway enrichment analysis and data visualisation techniques.
• Multiplex Immunofluorescence Image Analysis: In-depth analysis of immunofluorescence data, including cell density, infiltration patterns, cellular proximities, and detailed visualisation of results to support biological insights.
• Data Integration: We integrate diverse datasets from various technologies to identify common regulators and disease patterns. This integration is coupled with clinical data association and, when applicable, with machine learning tools to enhance predictive modelling and data interpretation.

All bioinformatics software and tools that we use for data analyses are offered free of charge for academic usage. Many of our established pipelines have been described previously in our recent publications.