About: Seamless integration of image and molecular analysis for spatial transcriptomics workflows

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Seamless integration of image and molecular analysis for spatial transcriptomics workflows
Creator	Lundeberg, Joakim Bergenstråhle, Joseph Larsson, Ludvig
Source	PMC
abstract	BACKGROUND: Recent advancements in in situ gene expression technologies constitute a new and rapidly evolving field of transcriptomics. With the recent launch of the 10x Genomics Visium platform, such methods have started to become widely adopted. The experimental protocol is conducted on individual tissue sections collected from a larger tissue sample. The two-dimensional nature of this data requires multiple consecutive sections to be collected from the sample in order to construct a comprehensive three-dimensional map of the tissue. However, there is currently no software available that lets the user process the images, align stacked experiments, and finally visualize them together in 3D to create a holistic view of the tissue. RESULTS: We have developed an R package named STUtility that takes 10x Genomics Visium data as input and provides features to perform standardized data transformations, alignment of multiple tissue sections, regional annotation, and visualizations of the combined data in a 3D model framework. CONCLUSIONS: STUtility lets the user process, analyze and visualize multiple samples of spatially resolved RNA sequencing and image data from the 10x Genomics Visium platform. The package builds on the Seurat framework and uses familiar APIs and well-proven analysis methods. An introduction to the software package is available at https://ludvigla.github.io/STUtility_web_site/.
has issue date	2020-07-16(xsd:dateTime)
bibo:doi	10.1186/s12864-020-06832-3
bibo:pmid	32664861
has license	cc-by
sha1sum (hex)	4fda96e73ecadb10024aeec3ed6d97405a825f03
schema:url	https://doi.org/10.1186/s12864-020-06832-3
resource representing a document's title	Seamless integration of image and molecular analysis for spatial transcriptomics workflows
has PubMed Central identifier	PMC7386244
has PubMed identifier	32664861
schema:publication	BMC Genomics
resource representing a document's body	covid:4fda96e73ecadb10024aeec3ed6d97405a825f03#body_text
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