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== Brendan Innes == Email: <<MailTo(brendan DOT innes AT mail DOT utoronto DOT ca)>> |
= Brendan Innes = Email: <<MailTo(brendan DOT innes AT mail DOT utoronto DOT ca)>><<BR>> Twitter: [[https://twitter.com/InnesBrendanT|@InnesBrendanT]]<<BR>> ORCID: [[https://orcid.org/0000-0003-2496-3154|0000-0003-2496-3154]]<<BR>> Looking for a place to discuss all things single-cell?<<BR>> [[https://bit.ly/scRNAseqTO|Join the Toronto scAnalysis Working Group Slack!]] ---- |
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=== Cell-cell interaction prediction === As part of our ongoing work developing tools to predict cell-cell interaction networks from -omics data, Ruth Isserlin has put together a [[http://www.baderlab.org/CellCellInteractions|handy database of ligand-receptor pairs]]. This database has powered analyses such as [[https://doi.org/10.1016/j.neuron.2016.07.037|this one from the Miller/Kaplan lab]], which identified extrinsic regulators of neurogenesis. |
== Projects == === CCInx - Cell-cell interaction prediction === As part of our ongoing work developing tools to predict cell-cell interaction networks from -omics data, Ruth Isserlin has put together a [[CellCellInteractions|handy database of ligand-receptor pairs]]. This database has powered analyses such as [[https://doi.org/10.1016/j.neuron.2016.07.037|this one from the Miller/Kaplan lab]], which identified extrinsic regulators of neurogenesis. I'm currently working on CCInx, an R package to generate and visualize bipartite graphs of cell-cell interactions from single-cell RNAseq data. A working development version is [[https://baderlab.github.io/CCInx|available here]]. '''Aging Mouse Brain'''<<BR>> [[https://hscrb.harvard.edu/people/methodios-ximerakis|Methodios Ximerakis]] and [[https://dbmi.hms.harvard.edu/people/scott-logan-lipnick|Scott Lipnick]] of [[https://hscrb.harvard.edu/lab/rubin-lab?|Lee Rubin's group]] are studying the effects of aging on the mammalian brain. We are collaborating with them to understand the changes in cell-cell signalling, predicted using CCInx. The results are available [[https://baderlab.github.io/AgingMouseBrainCCInx/|here]]. |
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I've built a simple pipeline and visualization tool to help collaborators go from raw gene expression counts per cell to exploring annotated cell-type specific gene expression data in a quick and reproducible way. Below is a quick video of an old prototype of the visualization tool in action, showing the sort of data one can get from this pipeline. [[https://baderlab.github.io/scClustViz|See the newest version here!]] | I've built an interactive reporting tool for single-cell RNAseq results called [[https://baderlab.github.io/scClustViz|scClustViz (or sCV for short)]]. Hopefully it will both help biologists and bioinformaticians better collaborate while working with this data, and improve open science by making it easier to publish data in an accessible manner. |
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{{attachment:scRNAseqViz.mp4|scRNAseqViz.mp4|width="800",title="",height="543"}} | '''Human Liver Atlas'''<<BR>> [[https://www.uhnresearch.ca/researcher/sonya-macparland|Sonya MacParland]] and [[https://www.uhnresearch.ca/researcher/ian-mcgilvray|Ian McGilvray]] led the creation of the first single-cell atlas of a human organ, the liver. Jeff Liu and I were honoured to perform the analysis for this project, the results of which can be viewed in [[https://baderlab.github.io/scClustViz/#human-liver-atlas|scClustViz here]]. |
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=== Education === | '''Embryonic Mouse Cerebral Cortex'''<<BR>> I worked with [[http://www.lmp.utoronto.ca/research/faculty-research-database/yuzwa-scott|Scott Yuzwa]] and [[https://lab.research.sickkids.ca/miller-kaplan/current-members/|Michael Borrett]] of Freda Miller's group to understand the precursor population responsible for building the mammalian cerebral cortex, and its relationship with adult neural stem cells. The single-cell transcriptomes from timepoints throughout cortical neurogenesis in the mouse brain can be viewed in [[https://baderlab.github.io/scClustViz/#embryonic-mouse-cerebral-cortex|scClustViz here]]. == Education == |
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=== Teaching Experience === TA for MBP1010H - Quantitative Biology and Statistical Methods |
== Teaching Experience == TA for MBP1010H - Quantitative Biology and Statistical Methods (2015 - 2017) |
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=== Publications === Ximerakis M, Lipnick SL, Simmons SK, Adiconis X, '''Innes BT''', Dionne D, Nguyen L, Mayweather BA, Ozek C, Niziolek Z, Butty VL, Isserlin R, Buchanan SM, Levine SR, Regev A, Bader GD, Levin JZ, Rubin LL. Single-cell transcriptomics of the aged mouse brain reveals convergent, divergent and unique aging signatures. ''Submitted to'' Nat Neurosci. ''Preprint at'' https://doi.org/10.1101/440032 |
TA for MMG1001 - Foundational Genetic Approaches I: Genomics (2019) == Publications == '''Innes BT''' & Bader GD. scClustViz – Single-cell RNAseq cluster assessment and visualization [version 2; peer review: 2 approved]. !F1000Res. 7:1522, 2019. http://doi.org/10.12688/f1000research.16198.2 Ximerakis M, Lipnick SL, '''Innes BT''', Simmons SK, Adiconis X, Dionne D, Nguyen L, Mayweather BA, Ozek C, Niziolek Z, Butty VL, Isserlin R, Buchanan SM, Levine SR, Regev A, Bader GD, Levin JZ, Rubin LL. Single-cell transcriptomic profiling of the aging mouse brain. ''Submitted to'' Nat Neurosci. ''Preprint at'' https://doi.org/10.1101/440032 |
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'''Innes BT''' & Bader GD. Innes BT and Bader GD. scClustViz – Single-cell RNAseq cluster assessment and visualization [version 1; referees: 2 approved with reservations]. !F1000Res. 7:1522, 2018. http://doi.org/10.12688/f1000research.16198.1 |
Brendan Innes
Email: <brendan DOT innes AT mail DOT utoronto DOT ca>
Twitter: @InnesBrendanT
ORCID: 0000-0003-2496-3154
Looking for a place to discuss all things single-cell?
Join the Toronto scAnalysis Working Group Slack!
I am a PhD candidate in Molecular Genetics who started in the Bader lab in May, 2016. I am very excited about the possibilities offered by high-throughput single-cell RNA-seq, especially to investigate intercellular signalling in complex tissues.
Projects
CCInx - Cell-cell interaction prediction
As part of our ongoing work developing tools to predict cell-cell interaction networks from -omics data, Ruth Isserlin has put together a handy database of ligand-receptor pairs. This database has powered analyses such as this one from the Miller/Kaplan lab, which identified extrinsic regulators of neurogenesis. I'm currently working on CCInx, an R package to generate and visualize bipartite graphs of cell-cell interactions from single-cell RNAseq data. A working development version is available here.
Aging Mouse Brain
Methodios Ximerakis and Scott Lipnick of Lee Rubin's group are studying the effects of aging on the mammalian brain. We are collaborating with them to understand the changes in cell-cell signalling, predicted using CCInx. The results are available here.
scClustViz - scRNAseq cluster assessment and visualization
I've built an interactive reporting tool for single-cell RNAseq results called scClustViz (or sCV for short). Hopefully it will both help biologists and bioinformaticians better collaborate while working with this data, and improve open science by making it easier to publish data in an accessible manner.
Human Liver Atlas
Sonya MacParland and Ian McGilvray led the creation of the first single-cell atlas of a human organ, the liver. Jeff Liu and I were honoured to perform the analysis for this project, the results of which can be viewed in scClustViz here.
Embryonic Mouse Cerebral Cortex
I worked with Scott Yuzwa and Michael Borrett of Freda Miller's group to understand the precursor population responsible for building the mammalian cerebral cortex, and its relationship with adult neural stem cells. The single-cell transcriptomes from timepoints throughout cortical neurogenesis in the mouse brain can be viewed in scClustViz here.
Education
MSc in Biochemistry at the University of Western Ontario, supervised by Dr. David Litchfield
BMSc in Cell Biology and Biochemistry at the University of Western Ontario
Teaching Experience
TA for MBP1010H - Quantitative Biology and Statistical Methods (2015 - 2017)
TA for MMG1001 - Foundational Genetic Approaches I: Genomics (2019)
Publications
Innes BT & Bader GD. scClustViz – Single-cell RNAseq cluster assessment and visualization [version 2; peer review: 2 approved]. F1000Res. 7:1522, 2019. http://doi.org/10.12688/f1000research.16198.2
Ximerakis M, Lipnick SL, Innes BT, Simmons SK, Adiconis X, Dionne D, Nguyen L, Mayweather BA, Ozek C, Niziolek Z, Butty VL, Isserlin R, Buchanan SM, Levine SR, Regev A, Bader GD, Levin JZ, Rubin LL. Single-cell transcriptomic profiling of the aging mouse brain. Submitted to Nat Neurosci. Preprint at https://doi.org/10.1101/440032
MacParland SA, Liu JC, Ma XZ, Innes BT, Bartczak AM, Gage BK, Manuel J, Khuu N, Echeverri J, Linares I, Gupta R, Cheng ML, Liu LY, Camat D, Chung SW, Seliga RK, Shao Z, Lee E, Ogawa S, Ogawa M, Wilson MD, Fish JE, Selzner M, Ghanekar A, Grant D, Greig P, Sapisochin G, Selzner N, Winegarden N, Adeyi O, Keller G, Bader GD, McGilvray ID. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun. 9(4383), 2018. https://doi.org/10.1038/s41467-018-06318-7
Yuzwa SA, Borrett MJ, Innes BT, Voronova A, Ketela T, Kaplan DR, Bader GD, Miller FD. Developmental Emergence of Adult Neural Stem Cells as Revealed by Single-Cell Transcriptional Profiling. Cell Rep. 21(13):3970-86, 2017. https://doi.org/10.1016/j.celrep.2017.12.017
Innes BT, Sowole MA, Gyenis L, Dubinsky M, Konermann L, Brandl CJ, Litchfield DW, Shilton BH. Peroxide-Mediated Oxidation and Inhibition of the Peptidyl-Prolyl Isomerase Pin1. Biochim Biophys Acta. 1852(5):905-12, 2015. https://doi.org/10.1016/j.bbadis.2014.12.025
Sowole MA, Innes BT, Amunugama M, Brandl CJ, Shilton BH, Litchfield DW, Konermann L. Noncovalent binding of a cyclic peptide inhibitor to the peptidyl-prolyl isomerase Pin1 explored by hydrogen exchange mass spectrometry. Can J Chem. July 2014. https://doi.org/10.1139/cjc-2014-0230
Innes BT, Bailey ML, Brandl CJ, Shilton BH, Litchfield DW. Non-catalytic participation of the Pin1 peptidyl-prolyl isomerase domain in target binding. Front. Physiol. 4:18, 2013. https://doi.org/10.3389/fphys.2013.00018