Research
Single-cell and short read sequencing
The Genome Innovation Hub continually develops a number of protocols and procedures while undertaking our collaborative projects. Below are a selection of detailed developments useful to researchers undertaking Single-cell and Short read sequencing procedures in the laboratory.
Developments
| Featured projects | Duration |
|---|---|
|
Ribosomal profiling with cellular specificity Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2023 |
|
High-throughput sequencing of protein variant libraries Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2023 |
|
Proximity ligation sequencing of mixed bacterial communities Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2023 |
|
Division-based single-cell-sequencing Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2022 |
|
Enrichment and analysis of siRNAs for topical RNAi applications. Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2022 |
|
Optimised bioinformatics and validation pipeline for genome-wide CRISPR screening data Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2021 |
|
RNA velocity quantification of single-cell transcriptomics Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2021 |
|
Expanding the scope of multimodal single cell sequencing Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2021 |
|
HTS single cell CRISPR technology for experimental validation of population genetics and functional genomics discovery Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2021 |
|
Understanding host-pathogen interactions through development of new co-transcriptomic single cell RNA sequencing technologies Genome Innovation Hub Collaborative Project (UQ infrastructure) |
2020 |
Pages
Publications & pre-prints
Genotype-free demultiplexing of pooled single-cell RNA-seq
Jun Xu, Caitlin Falconer, Quan Nguyen, Joanna Crawford, Brett D. McKinnon, Sally Mortlock, Anne Senabouth, Stacey Andersen, Han Sheng Chiu, Longda Jiang, Nathan J. Palpant, Jian Yang, Michael D. Mueller, Alex W. Hewitt, Alice Pébay, Grant W. Montgomery, Joseph E. Powell & Lachlan J.M Coin
Genome Biology volume 20, Article number: 290 (2019)
Andrew Su, HoJoon Lee, Xiao Tan, Carlos J. Suarez, Noemi Andor, Quan Nguyen, Hanlee P. Ji
bioRxiv 2021.03.18.436004; doi: https://doi.org/10.1101/2021.03.18.436004
Arti M. Raghubar, Duy T. Pham, Xiao Tan, Laura F. Grice, Joanna Crawford, Pui Yeng Lam, Stacey B. Andersen, Sohye Yoon, Monica S.Y. Ng, Siok Min Teoh, Samuel E. Holland, Anne Stewart, Leo Francis, Alexander N. Combes, Andrew J. Kassianos, Helen Healy, Quan Nguyen, Andrew J. Mallett
bioRxiv 2020.09.29.317917; doi: https://doi.org/10.1101/2020.09.29.317917
M Tran, S Yoon, M Teoh, S Andersen, PY Lam, P Purdue, A Raghubar, SJ Hanson, K Devitt, K Jones, S Walters, ZK Tuong, A Kulasinghe, J Monkman, HP Soyer, I Frazer, Q Nguyen.
https://doi.org/10.1101/2020.09.10.290833
Duy Pham, Xiao Tan, Jun Xu, Laura F. Grice, Pui Yeng Lam, Arti Raghubar, Jana Vukovic, Marc J. Ruitenberg, Quan Nguyen
bioRxiv 2020.05.31.125658; doi: https://doi.org/10.1101/2020.05.31.125658
SpaCell: integrating tissue morphology and spatial gene expression to predict disease cells.
Xiao Tan, Andrew Su, Minh Tran, Quan Nguyen
Bioinformatics, Volume 36, Issue 7, 1 April 2020, Pages 2293–2294
