Publications

Methodology and tools

Preprint

  • Yin, D., Cao, Y., Chen, J., Mak, C. L., Yu, K. H., Lin, Y., Ho, J.W.K. & Yang, J.Y.H. (2022). Covidscope: An atlas-scale COVID-19 resource for single-cell meta analysis at sample and cell levels. BioRxiv. [paper]

2024

  • Lin, Y., Wu, T. Y., Chen, X., Wan, S., Chao, B., Xin, J., Yang, J.Y.H & Wang, Wong W.H., Wang R.Y.X. (2022). scTIE: data integration and inference of gene regulation using single-cell temporal multimodal data. Genome Res. [paper]

2023

  • Couto, B. Z. P., Robertson, N., Patrick, E., & Ghazanfar, S. (2023). MoleculeExperiment enables consistent infrastructure for molecule-resolved spatial transcriptomics data in Bioconductor. Accepted by Bioinformatics [paper]

  • Yu, L., Liu, C., Yang, J.Y.H., & Yang, P. (2023). Ensemble deep learning of embeddings for clustering multimodal single-cell omics data. Bioinformatics. [paper]

  • Lin, Y., Cao, Y., Willie, E., Patrick, E., & Yang, J. Y. H. (2023). Atlas-scale single-cell multi-sample multi-condition data integration using scMerge2. Nature Communications. [paper]

  • Ghazanfar, S., Guibentif, C., & Marioni, J. C. (2023). Stabilized mosaic single-cell data integration using unshared features. Nature Biotechnology, 1-9. [paper]

  • Liu, C., Huang, H., & Yang, P. (2023). Multi-task learning from multimodal single-cell omics with Matilda. Nucleic Acids Research, 51(8), e45-e45. [paper]

  • Patrick, E., Canete, N. P., Baharlou, H., Iyengar, S. S., Harman, A. N., Sutherland, G. T., and Yang P. (2021). Spatial analysis for highly multiplexed imaging data to identify tissue microenvironments. Cytometry A. [package][shiny][paper]

  • Cao, Y., Ghazanfar, S., Yang, P., & Yang, J.Y.H. (2023). Benchmarking of analytical combinations for COVID-19 outcome prediction using single-cell RNA sequencing data. Briefings in Bioinformatics. [paper]

  • Cao, Y., Tran, A., Kim, H., Robertson, N., Lin, Y., Torkel, M., Yang, P., Patrick, E., Ghazanfar, S., & Yang, J.Y.H. (2023). Thinking process templates for constructing data stories with SCDNEY. F1000 Research. [paper]

  • Yu, L., Cao, Y., Yang, J.Y.H., & Yang, P. (2022). Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data. Genome Biology. [paper]

2022

  • Canete, N. P., Iyengar, S. S., Wilmott. J. S., Ormerod, J. T., Harman, A. N., and Patrick, E.(2021) spicyR: Spatial analysis of in situ cytometry data in R. Bioinformatics. [package][shiny][paper]

  • Cao, Y., Lin, Y., Patrick, E., Yang, P., and Yang, J.Y.H. (2022) scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction. Bioinformatics. [paper]

  • Lin, Y., Wu, T.Y., Wan, S., Yang, J.Y.H., Wong, W.H., and Wang, Y.X.R. (2022) scJoint: transfer learning for data integration of single-cell RNA-seq and ATAC-seq. Nature Biotechnology. [package][paper]

  • Tran, A., Yang P., Yang, J.Y.H., and Ormerod, J. T. (2022) scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model. NAR Genomics and Bioinformaitics. [package][paper]

2021

  • Kim, H.J., Wang, K.Y., Chen, C., Lin, Y., Tam, P., Lin, D.M., Yang, J.Y.H. and Yang, P. (2021) Uncovering cell identity through differential stability with Cepo. Nature Computational Science. [package][paper]

  • Cao, Y., Yang, P., and Yang, J.Y.H. (2021) A benchmark study of simulation methods for single-cell RNA sequencing data. Nature Communications. [package][paper]

  • Chan, A., Jiang W., Blyth E., Yang, J.Y.H., and Patrick, E. (2021) treekoR: identifying cellular-to-phenotype associations by elucidating hierarchical relationships in high-dimensional cytometry data. Genome Biology. [package][paper]

  • Yang, P., Huang, H., and Liu, C. (2021) Feature selection revisited in the single-cell era. Genome Biology. [paper]

  • Baharlou, H., Canete, N. P., Bertram, K. M., Sandgren, K. J., Cunningham, A. L., Harman, A. N., and Patrick, E. (2021). AFid: a tool for automated identification and exclusion of autofluorescent objects from microscopy images. Bioinformatics, 37(4):559–567. [paper]

2020

  • Ghazanfar, S., Lin, Y., Su, X., Lin, D.M., Patrick, E., Han, Z.G., Marioni, J.C., and Yang, J.Y.H. (2020) Investigating higher-order interactions in single-cell data with scHOT. Nature Methods. [package][paper]

  • Lin, Y., Cao, Y., Kim, H.J., Salim, A., Speed, T., Lin, D.M., Yang, P. and Yang, J.Y.H. (2020) scClassify: sample size estimation and multiscale classification of cells using single and multiple reference. Molecular Systems Biology. [package][shiny][paper]

  • Kim, H.J., Lin, Y., Geddes, T.A., Yang, J.Y.H. and Yang, P. (2020) CiteFuse enables multi-modal analysis of CITE-seq data. Bioinformatics. [package][shiny][paper]

  • Patrick, R., Humphreys, D.T., Janbandhu, V., Oshlack, A., Ho, J.W.K., Harvey, R.P., Lo, K.K. (2020) Sierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data. Genome Biology. [package][paper]

  • Patrick, E., Taga, M., Ergun, A., Ng, B., Casazza, W., Cimpean, M., Yung, C., Schneider, J. A., Bennett, D. A., Gaiteri, C., Jager, P. L. D., Bradshaw, E. M., and Mostafavi, S. (2020). Deconvolving the contributions of cell-type heterogeneity on cortical gene expression. PLOS Computational Biology, 16(8):e1008120.[paper]

2019

  • Lin, Y., Ghazanfar, S., Wang, K.Y., Gagnon-Bartsch, J.A., Lo, K.K., Su, X., Han, Z.G., Ormerod, J.T., Speed, T.P., Yang, P. and Yang, J.Y.H. (2019) scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets. Proceedings of the National Academy of Sciences. [package] [paper]

  • Geddes, T., Kim, T., Nan, L., Burchfield, J., Yang, J.Y.H., Tao, D. and Yang, P. (2019) Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis. BMC Bioinformatics. [package] [paper]

  • Cao, Y., Lin, Y., Ormerod, J., Yang, P., Yang, J.Y.H. & Lo, K. (2019) scDC: single cell differential composition analysis. BMC Bioinformatics. [package] [paper]

  • Kim, T., Lo, K., Geddes, T., Kim, H.J., Yang, J.Y.H. & Yang, P. (2019) scReClassify: post hoc cell type classification of single-cell RNA-seq data. BMC Genomics. [package] [paper]

  • Lin, Y., Ghazanfar, S., Strbenac, D., Wang, A., Patrick, E., Lin, D., Speed, T., Yang, J.Y.H. & Yang, P. (2019) Evaluating stably expressed genes in single cells. GigaScience. [package] [paper]

  • Baharlou, H., Canete, N. P., Cunningham, A. L., Harman, A. N., and Patrick, E. (2019). Mass Cytometry Imaging for the Study of Human Diseases—Applications and Data Analysis Strategies. Frontiers in Immunology, 10.[paper]

2018

  • Kim, T., Chen, I., Lin, Y., Wang, A., Yang, J.Y.H. and Yang, P. (2018) Impact of similarity metrics on single-cell RNA-seq data clustering. Briefings in Bioinformatics. [package][paper]

2016

  • Ghazanfar, S., Bisogni, A., Ormerod, J.T.,, Lin, D.M., and Yang, J.Y.H. (2016) Integrated single cell data analysis reveals cell specific networks and novel coactivation markers. BMC Systems Biology. [paper]

Applications

  • Kim, H.J., O’Hara-Wright, M., Kim, D., Loi, T. H., Lim, B. Y., Jamieson, R. V., … & Yang, P. (2023). Comprehensive characterization of fetal and mature retinal cell identity to assess the fidelity of retinal organoids. Stem Cell Reports, 18(1), 175-189. [paper]

  • Lin, Y., Loo, L., Tran, A., Lin, D. M., Moreno, C., Hesselson, D., Neely G.G., & Yang, J.Y. (2022). Scalable workflow for characterization of cell-cell communication in COVID-19 patients. PLOS Computational Biology, 18(10), e1010495. [paper]

  • Su, X., Zhao, L.N., Shi, Y., Zhang, R., Long, Q., Bai, S., Luo, Q., Lin Y.,, Zou, X., Ghazanfar, S.,, Tao, Kun., Yang, G., Wang, L., He, K.Y., Cui, X., He, J., Wu, J.X., Han, B., Wang, N., Li, X., Yang, P., Hou, S., Sun, J., Yang, J.Y.H., Chen, J. and Han, Z.G. (2021) Single-cell and single-variant resolution analysis of clonal evolution in human liver cancer. Journal of Hematology & Oncology. [paper]

  • Singh, R., Cottle, L., Loudovaris, T., Xiao, D., Yang. P., Thomas, H., Kebede, A. M., and Thorn, P. (2020) Enhanced structure and function of human pluripotent stem cell-derived beta-cells cultured on extracellular matrix. Stem cells translational medicine. [paper]

  • Su, X., Long, Q., Bo, J., Shi, Y., Zhao, L.N., Lin Y., Luo, Q., Ghazanfar, S., Zhang, C., Liu, Q., Wang, L., He, K., He, J., Cui, X., Yang, J.Y.H., Han, Z.G., Yang, G., and Sha, J.J. (2020) Mutational and transcriptomic landscapes of a rare human prostate basal cell carcinoma. The Prostate. [paper]

  • McGuire, H. M., Rizzetto, S., Withers, B. P., Clancy, L. E., Avdic, S., Stern, L., Patrick, E., Groth, B. F. d. S., Slobedman, B., Gottlieb, D. J., Luciani, F., and Blyth, E. (2020). Mass cytometry reveals immune signatures associated with cytomegalovirus (CMV) control in recipients of allogeneic haemopoietic stem cell transplant and CMV-specific T cells. Clinical & Translational Immunology, 9(7):e1149.

  • Jimenez Vera, E., Chew, Y. V., Nicholson, L., Burns, H., Anderson, P., Chen, H.-T., Williams, L., Keung, K., Zanjani, N. T., Dervish, S., Patrick, E., Wang, X. M., Yi, S., Hawthorne, W., Alexander, S., O’Connell, P. J., and Hu, M. (2019). Standardisation of flow cytometry for whole blood immunopheno-typing of islet transplant and transplant clinical trial recipients. PLoS ONE, 14(5).

  • He J., Lin Y.,, Su, X., Luo, Q., Ghazanfar, S., Yang, J.Y.H. and Han,Z.G. (2019) Single-Cell RNA-Seq Reveals Naïve B cells Associated with Better Prognosis of HCC. Biorxiv. [paper]

  • Su, X., Shi, Y., Zou, X., Lu, Z.N., Xie, G., Yang, J.Y.H., Wu, C.C., Cui., X.F., He, K.Y., Luo, Q., Qu, Y.L., Wang, N., Wang, L., Han, Z.G. (2017) Single-cell RNA-Seq analysis reveals dynamic trajectories during mouse liver development BMC Genomics. [paper]