The complete solution and interpretation algorithms for large field-of-view and high-resolution spatial transcriptomics
Конференцијски прилог (Објављена верзија)
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© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
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The large field-of-view and high-resolution spatial transcriptomics technology can
reveal and answer scientific questions that cannot be discovered or elucidated by lowresolution
spatial transcriptomics. Obtaining expression profiles at the single-cell level
from high-resolution spatial transcriptomics requires sophisticated data processing and
interpretation strategies, including extensive image data processing, transcriptome data
processing, integration analysis. At the same time, the introduction of spatial information
helps with the annotation of single cells at the tissue level and the study of tissue
structure and function, while cell clustering and cell annotation are important foundations
for subsequent in-depth analysis. Cell annotation can be divided into clustering and reannotation
based on marker genes and end-to-end cell annotation based on reference
datasets. The choice between the two depends on whether markers are easier to obtain
or whether reference dataset...s with consistent data backgrounds are easier to obtain. The
algorithm team at BGI Research Institute has conducted extensive algorithm research
and development on data interpretation strategies, cell clustering algorithms, and cell
annotation algorithms for large field-of-view and high-resolution spatial transcriptomics
technology, with the aim of providing comprehensive, efficient, and highly reliable data
analysis algorithms, tools and platform support.
Кључне речи:
spatial transcriptomics technologyИзвор:
4th Belgrade Bioinformatics Conference, 2023, 4, 34-34Издавач:
- Belgrade : Institute of molecular genetics and genetic engineering
Напомена:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Колекције
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Fang, Shuangsang PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/1969 AB - The large field-of-view and high-resolution spatial transcriptomics technology can reveal and answer scientific questions that cannot be discovered or elucidated by lowresolution spatial transcriptomics. Obtaining expression profiles at the single-cell level from high-resolution spatial transcriptomics requires sophisticated data processing and interpretation strategies, including extensive image data processing, transcriptome data processing, integration analysis. At the same time, the introduction of spatial information helps with the annotation of single cells at the tissue level and the study of tissue structure and function, while cell clustering and cell annotation are important foundations for subsequent in-depth analysis. Cell annotation can be divided into clustering and reannotation based on marker genes and end-to-end cell annotation based on reference datasets. The choice between the two depends on whether markers are easier to obtain or whether reference datasets with consistent data backgrounds are easier to obtain. The algorithm team at BGI Research Institute has conducted extensive algorithm research and development on data interpretation strategies, cell clustering algorithms, and cell annotation algorithms for large field-of-view and high-resolution spatial transcriptomics technology, with the aim of providing comprehensive, efficient, and highly reliable data analysis algorithms, tools and platform support. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - The complete solution and interpretation algorithms for large field-of-view and high-resolution spatial transcriptomics EP - 34 SP - 34 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_1969 ER -
@conference{ author = "Fang, Shuangsang", year = "2023", abstract = "The large field-of-view and high-resolution spatial transcriptomics technology can reveal and answer scientific questions that cannot be discovered or elucidated by lowresolution spatial transcriptomics. Obtaining expression profiles at the single-cell level from high-resolution spatial transcriptomics requires sophisticated data processing and interpretation strategies, including extensive image data processing, transcriptome data processing, integration analysis. At the same time, the introduction of spatial information helps with the annotation of single cells at the tissue level and the study of tissue structure and function, while cell clustering and cell annotation are important foundations for subsequent in-depth analysis. Cell annotation can be divided into clustering and reannotation based on marker genes and end-to-end cell annotation based on reference datasets. The choice between the two depends on whether markers are easier to obtain or whether reference datasets with consistent data backgrounds are easier to obtain. The algorithm team at BGI Research Institute has conducted extensive algorithm research and development on data interpretation strategies, cell clustering algorithms, and cell annotation algorithms for large field-of-view and high-resolution spatial transcriptomics technology, with the aim of providing comprehensive, efficient, and highly reliable data analysis algorithms, tools and platform support.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "The complete solution and interpretation algorithms for large field-of-view and high-resolution spatial transcriptomics", pages = "34-34", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_1969" }
Fang, S.. (2023). The complete solution and interpretation algorithms for large field-of-view and high-resolution spatial transcriptomics. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 34-34. https://hdl.handle.net/21.15107/rcub_imagine_1969
Fang S. The complete solution and interpretation algorithms for large field-of-view and high-resolution spatial transcriptomics. in 4th Belgrade Bioinformatics Conference. 2023;4:34-34. https://hdl.handle.net/21.15107/rcub_imagine_1969 .
Fang, Shuangsang, "The complete solution and interpretation algorithms for large field-of-view and high-resolution spatial transcriptomics" in 4th Belgrade Bioinformatics Conference, 4 (2023):34-34, https://hdl.handle.net/21.15107/rcub_imagine_1969 .