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Book ; Online: Comparative Analysis of Packages and Algorithms for the Analysis of Spatially Resolved Transcriptomics Data

Charitakis, Natalie / Ramialison, Mirana / Nim, Hieu T.

2021

Abstract: The technology to generate Spatially Resolved Transcriptomics (SRT) data is rapidly being improved and applied to investigate a variety of biological tissues. The ability to interrogate how spatially localised gene expression can lend new insight to ... ...

Abstract	The technology to generate Spatially Resolved Transcriptomics (SRT) data is rapidly being improved and applied to investigate a variety of biological tissues. The ability to interrogate how spatially localised gene expression can lend new insight to different tissue development is critical, but the appropriate tools to analyse this data are still emerging. This chapter reviews available packages and pipelines for the analysis of different SRT datasets with a focus on identifying spatially variable genes (SVGs) alongside other aims, while discussing the importance of and challenges in establishing a standardised 'ground truth' in the biological data for benchmarking. Comment: 32 pages, Figures 3
Keywords	Quantitative Biology - Quantitative Methods ; Quantitative Biology - Genomics
Publishing date	2021-08-03
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: From whole-mount to single-cell spatial assessment of gene expression in 3D.

Waylen, Lisa N / Nim, Hieu T / Martelotto, Luciano G / Ramialison, Mirana

Communications biology

2020 Volume 3, Issue 1, Page(s) 602

Abstract: Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene ...

Abstract	Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene expression data. Novel techniques expand on current benchmark protocols, expediting their incorporation into ongoing research. These approaches digitally reconstruct patterns of embryonic expression in three dimensions, and have successfully identified novel domains of expression, cell types, and tissue features. Such technologies pave the way for unbiased and exhaustive recapitulation of gene expression levels in spatial and quantitative terms, promoting understanding of the molecular origin of developmental defects, and improving medical diagnostics.
MeSH term(s)	Animals ; Embryonic Development/genetics ; Gene Expression Profiling/methods ; Gene Expression Regulation, Developmental ; High-Throughput Nucleotide Sequencing ; Humans ; Molecular Imaging ; Organ Specificity/genetics ; Single-Cell Analysis/methods ; Transcriptome
Language	English
Publishing date	2020-10-23
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ISSN	2399-3642
ISSN (online)	2399-3642
DOI	10.1038/s42003-020-01341-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Spatially resolved transcriptomics in immersive environments.

Bienroth, Denis / Nim, Hieu T / Garkov, Dimitar / Klein, Karsten / Jaeger-Honz, Sabrina / Ramialison, Mirana / Schreiber, Falk

Visual computing for industry, biomedicine, and art

2022 Volume 5, Issue 1, Page(s) 2

Abstract: Spatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the subsequent ...

Abstract	Spatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the subsequent interpretation and visualization of the datasets acquired. To address this challenge, VR-Cardiomics is presented, which is a novel data visualization system with interactive functionalities designed to help biologists interpret spatially resolved transcriptomic datasets. By implementing the system in two separate immersive environments, fish tank virtual reality (FTVR) and head-mounted display virtual reality (HMD-VR), biologists can interact with the data in novel ways not previously possible, such as visually exploring the gene expression patterns of an organ, and comparing genes based on their 3D expression profiles. Further, a biologist-driven use-case is presented, in which immersive environments facilitate biologists to explore and compare the heart expression profiles of different genes.
Language	English
Publishing date	2022-01-10
Publishing country	Germany
Document type	Journal Article
ISSN	2524-4442
ISSN (online)	2524-4442
DOI	10.1186/s42492-021-00098-6
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Article ; Online: Spatially resolved transcriptomics in immersive environments

Denis Bienroth / Hieu T. Nim / Dimitar Garkov / Karsten Klein / Sabrina Jaeger-Honz / Mirana Ramialison / Falk Schreiber

Visual Computing for Industry, Biomedicine, and Art, Vol 5, Iss 1, Pp 1-

2022 Volume 13

Abstract: Abstract Spatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the ... ...

Abstract	Abstract Spatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the subsequent interpretation and visualization of the datasets acquired. To address this challenge, VR-Cardiomics is presented, which is a novel data visualization system with interactive functionalities designed to help biologists interpret spatially resolved transcriptomic datasets. By implementing the system in two separate immersive environments, fish tank virtual reality (FTVR) and head-mounted display virtual reality (HMD-VR), biologists can interact with the data in novel ways not previously possible, such as visually exploring the gene expression patterns of an organ, and comparing genes based on their 3D expression profiles. Further, a biologist-driven use-case is presented, in which immersive environments facilitate biologists to explore and compare the heart expression profiles of different genes.
Keywords	Spatially-resolved transcriptomics ; Spatial transcriptomics ; Virtual reality ; Fish tank virtual reality ; Head-mounted display ; Immersive analytics ; Drawing. Design. Illustration ; NC1-1940 ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Computer software ; QA76.75-76.765
Subject code	004 ; 629
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: From whole-mount to single-cell spatial assessment of gene expression in 3D

Lisa N. Waylen / Hieu T. Nim / Luciano G. Martelotto / Mirana Ramialison

Communications Biology, Vol 3, Iss 1, Pp 1-

2020 Volume 11

Abstract: In this Review, Lisa Waylen and colleagues provide an overview of techniques used for spatial resolution of gene expression in a tissue or organ. They discuss the advantages, disadvantages and future directions of current methods and illustrate how ... ...

Abstract	In this Review, Lisa Waylen and colleagues provide an overview of techniques used for spatial resolution of gene expression in a tissue or organ. They discuss the advantages, disadvantages and future directions of current methods and illustrate how spatial transcriptomics has impacted our understanding of biology.
Keywords	Biology (General) ; QH301-705.5
Language	English
Publishing date	2020-10-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Towards spatio-temporally resolved developmental cardiac gene regulatory networks in zebrafish.

Hallab, Jeannette C / Nim, Hieu T / Stolper, Julian / Chahal, Gulrez / Waylen, Lisa / Bolk, Francesca / Elliott, David A / Porrello, Enzo / Ramialison, Mirana

Briefings in functional genomics

2021

Abstract: Heart formation in the zebrafish involves a rapid, complex series of morphogenetic events in three-dimensional space that spans cardiac lineage specification through to chamber formation and maturation. This process is tightly orchestrated by a cardiac ... ...

Abstract	Heart formation in the zebrafish involves a rapid, complex series of morphogenetic events in three-dimensional space that spans cardiac lineage specification through to chamber formation and maturation. This process is tightly orchestrated by a cardiac gene regulatory network (GRN), which ensures the precise spatio-temporal deployment of genes critical for heart formation. Alterations of the timing or spatial localisation of gene expression can have a significant impact in cardiac ontogeny and may lead to heart malformations. Hence, a better understanding of the cellular and molecular basis of congenital heart disease relies on understanding the behaviour of cardiac GRNs with precise spatiotemporal resolution. Here, we review the recent technical advances that have expanded our capacity to interrogate the cardiac GRN in zebrafish. In particular, we focus on studies utilising high-throughput technologies to systematically dissect gene expression patterns, both temporally and spatially during heart development.
Language	English
Publishing date	2021-06-25
Publishing country	England
Document type	Journal Article
ZDB-ID	2540916-5
ISSN	2041-2657 ; 2041-2649 ; 2041-2647
ISSN (online)	2041-2657
ISSN	2041-2649 ; 2041-2647
DOI	10.1093/bfgp/elab030
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Article ; Online: Algorithm for calculating high disease activity in SLE.

Hoi, Alberta / Nim, Hieu T / Koelmeyer, Rachel / Sun, Ying / Kao, Amy / Gunther, Oliver / Morand, Eric

Rheumatology (Oxford, England)

2021 Volume 60, Issue 9, Page(s) 4291–4297

Abstract: Background: The ability to identify lupus patients in high disease activity status (HDAS) without knowledge of the SLEDAI could have application in selection of patients for treatment escalation or enrolment in trials. We sought to generate an algorithm ...

Abstract	Background: The ability to identify lupus patients in high disease activity status (HDAS) without knowledge of the SLEDAI could have application in selection of patients for treatment escalation or enrolment in trials. We sought to generate an algorithm that could calculate via model fitting the presence of HDAS using simple demographic and laboratory values. Methods: We examined the association of high disease activity (HDA) with demographic and laboratory parameters using prospectively collected data. An HDA visit is recorded when SLEDAI-2K ≥10. We utilized the use of combinatorial search to find algorithms to build a mathematical model predictive of HDA. Performance of each algorithm was evaluated using multi-class area under the receiver operating characteristic curve and the final model was compared with the naïve Bayes classifier, and analysed using the confusion matrix for accuracy and misclassification rate. Results: Data on 286 patients, followed for a median of 5.1 years were studied for a total of 5680 visits. Sixteen laboratory parameters were found to be significantly associated with HDA. A total of 216 algorithms were evaluated and the final algorithm chosen was based on seven pathology measures and three demographic variables. It has an accuracy of 88.6% and misclassification rate of 11.4%. When compared with the naïve Bayes classifier [area under the curve (AUC) = 0.663], our algorithm has a better accuracy with AUC = 0.829. Conclusion: This study shows that building an accurate model to calculate HDA using routinely available clinical parameters is feasible. Future studies to independently validate the algorithm will be needed to confirm its predictive performance.
MeSH term(s)	Adolescent ; Adult ; Age Factors ; Algorithms ; Female ; Humans ; Lupus Erythematosus, Systemic/diagnosis ; Male ; Middle Aged ; Prognosis ; Severity of Illness Index ; Young Adult
Language	English
Publishing date	2021-02-10
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1464822-2
ISSN	1462-0332 ; 1462-0324
ISSN (online)	1462-0332
ISSN	1462-0324
DOI	10.1093/rheumatology/keab003
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Article ; Online: CD90 Marks a Mesenchymal Program in Human Thymic Epithelial Cells

Sun, Shicheng / Li, Jacky Y / Nim, Hieu T / Piers, Adam / Ramialison, Mirana / Porrello, Enzo R / Konstantinov, Igor E / Elefanty, Andrew G / Stanley, Edouard G

Frontiers in immunology

2022 Volume 13, Page(s) 846281

Abstract: Thymic epithelium is critical for the structural integrity of the thymus and for T cell development ...

Abstract	Thymic epithelium is critical for the structural integrity of the thymus and for T cell development. Within the fully formed thymus, large numbers of hematopoietic cells shape the thymic epithelium into a scaffold-like structure which bears little similarity to classical epithelial layers, such as those observed in the skin, intestine or pancreas. Here, we show that human thymic epithelial cells (TECs) possess an epithelial identity that also incorporates the expression of mesenchymal cell associated genes, whose expression levels vary between medullary and cortical TECs (m/cTECs). Using pluripotent stem cell (PSC) differentiation systems, we identified a unique population of cells that co-expressed the master TEC transcription factor
MeSH term(s)	Cell Differentiation ; Epithelial Cell Adhesion Molecule/genetics ; Epithelial Cells/metabolism ; Epithelium ; Humans ; RNA/metabolism ; Thy-1 Antigens/metabolism ; Thymus Gland
Chemical Substances	Epithelial Cell Adhesion Molecule ; Thy-1 Antigens ; RNA (63231-63-0)
Language	English
Publishing date	2022-03-16
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2022.846281
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Article ; Online: Disease course following High Disease Activity Status revealed patterns in SLE.

Hoi, Alberta / Koelmeyer, Rachel / Bonin, Julie / Sun, Ying / Kao, Amy / Gunther, Oliver / Nim, Hieu T / Morand, Eric

Arthritis research & therapy

2021 Volume 23, Issue 1, Page(s) 191

Abstract: Background: We sought to examine the disease course of High Disease Activity Status (HDAS) patients and their different disease patterns in a real-world longitudinal cohort. Disease resolution till Lupus Low Disease Activity State (LLDAS) has been a ... ...

Abstract	Background: We sought to examine the disease course of High Disease Activity Status (HDAS) patients and their different disease patterns in a real-world longitudinal cohort. Disease resolution till Lupus Low Disease Activity State (LLDAS) has been a general treatment goal, but there is limited information on this subset of patients who achieve this. Methods: All consenting patients of the Monash Lupus Cohort who had at least 12 months of observation were included. HDAS was defined as SLEDAI-2K ≥ 10 ever, and HDAS episode as the period from the first HDAS clinic visit until attainment of LLDAS. We examined the associations of different HDAS patterns with the likelihood of damage accrual. Results: Of 342 SLE patients, 151 experienced HDAS at least once, accounting for 298 HDAS episodes. The majority of HDAS patients (76.2%) experienced Recurrent HDAS (> 1 HDAS visit), and a smaller subset (47.7%) had Persistent HDAS (consecutive HDAS visits for longer than 2 months). Recurrent or Persistent HDAS patients were younger at diagnosis and more likely to experience renal or serositis manifestations; persistent HDAS patients were also more likely to experience neurological manifestations. Baseline SLEDAI greater than 10 was associated with longer HDAS episodes. Recurrent and Persistent HDAS were both associated with an increased likelihood of damage accrual. The total duration of HDAS episode greater than 2 years and experiencing multiple HDAS episodes (≥4) was also associated with an increased likelihood of damage accrual (OR 1.80, 95% CI 1.08-2.97, p = 0.02, and OR 3.31, 95% CI 1.66-13.26, p = 0.01, respectively). Conclusion: HDAS episodes have a highly variable course. Recurrent and Persistent HDAS, and longer duration of HDAS episodes, increased the risk of damage accrual. In addition to a major signifier of severity in SLE, its resolution to LLDAS can determine the subsequent outcome in SLE patients.
MeSH term(s)	Cohort Studies ; Disease Progression ; Humans ; Lupus Erythematosus, Systemic/diagnosis ; Lupus Erythematosus, Systemic/epidemiology ; Severity of Illness Index ; Time Factors
Language	English
Publishing date	2021-07-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2107602-9
ISSN	1478-6362 ; 1478-6354
ISSN (online)	1478-6362
ISSN	1478-6354
DOI	10.1186/s13075-021-02572-1
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Article ; Online: MonaGO: a novel gene ontology enrichment analysis visualisation system.

Xin, Ziyin / Cai, Yujun / Dang, Louis T / Burke, Hannah M S / Revote, Jerico / Charitakis, Natalie / Bienroth, Denis / Nim, Hieu T / Li, Yuan-Fang / Ramialison, Mirana

BMC bioinformatics

2022 Volume 23, Issue 1, Page(s) 69

Abstract: Background: Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented ...

Abstract	Background: Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is still lacking. Results: Monash Gene Ontology (MonaGO) is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing GO enrichment analysis and visualising the results. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is a unique platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options. Conclusion: MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.
MeSH term(s)	Cluster Analysis ; Gene Ontology ; Probability ; Reproducibility of Results ; Software
Language	English
Publishing date	2022-02-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-022-04594-1
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