Spatial Transcriptomics: Technical Aspects of Recent Developments and Their Applications in Neuroscience and Cancer Research
Sign Up to like & getrecommendations! Published in 2023 at "Advanced Science"
DOI: 10.1002/advs.202206939
Abstract: Spatial transcriptomics is a newly emerging field that enables high‐throughput investigation of the spatial localization of transcripts and related analyses in various applications for biological systems. By transitioning from conventional biological studies to “in situ”… read more here.
Keywords: transcriptomics technical; technical aspects; neuroscience cancer; applications neuroscience ... See more keywords
Role for kappa-opioid system in stress-induced cocaine use uncovered with PET
Sign Up to like & getrecommendations! Published in 2019 at "Neuropsychopharmacology"
DOI: 10.1038/s41386-019-0512-7
Abstract: 1. Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenomewide association studies. Genome Biol. 2014;15:R31. 2. Zheng SC, Breeze CE, Beck S, Teschendorff AE. Identification of differentially methylated cell types in epigenome-wide… read more here.
Keywords: science; spatial transcriptomics; opioid system; role kappa ... See more keywords
DestVI identifies continuums of cell types in spatial transcriptomics data.
Sign Up to like & getrecommendations! Published in 2022 at "Nature biotechnology"
DOI: 10.1038/s41587-022-01272-8
Abstract: Most spatial transcriptomics technologies are limited by their resolution, with spot sizes larger than that of a single cell. Although joint analysis with single-cell RNA sequencing can alleviate this problem, current methods are limited to… read more here.
Keywords: destvi; destvi identifies; cell types; identifies continuums ... See more keywords
STARCH: copy number and clone inference from spatial transcriptomics data
Sign Up to like & getrecommendations! Published in 2020 at "Physical Biology"
DOI: 10.1088/1478-3975/abbe99
Abstract: Tumors are highly heterogeneous, consisting of cell populations with both transcriptional and genetic diversity. These diverse cell populations are spatially organized within a tumor, creating a distinct tumor microenvironment. A new technology called spatial transcriptomics… read more here.
Keywords: copy number; spatial transcriptomics; transcriptomics data; number ... See more keywords
DIST: spatial transcriptomics enhancement using deep learning
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad013
Abstract: Spatially resolved transcriptomics technologies enable comprehensive measurement of gene expression patterns in the context of intact tissues. However, existing technologies suffer from either low resolution or shallow sequencing depth. Here, we present DIST, a deep… read more here.
Keywords: dist spatial; deep learning; gene expression; spatial transcriptomics ... See more keywords
Identifying spatial domain by adapting transcriptomics with histology through contrastive learning
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad048
Abstract: Recent advances in spatial transcriptomics have enabled measurements of gene expression at cell/spot resolution meanwhile retaining both the spatial information and the histology images of the tissues. Accurately identifying the spatial domains of spots is… read more here.
Keywords: spatial transcriptomics; histology; gene expression; identifying spatial ... See more keywords
Assessing heterogeneity in spatial data using the HTA index with applications to spatial transcriptomics and imaging.
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab569
Abstract: MOTIVATION Tumour heterogeneity is being increasingly recognised as an important characteristic of cancer and as a determinant of prognosis and treatment outcome. Emerging spatial transcriptomics data hold the potential to further our understanding of tumour… read more here.
Keywords: data using; heterogeneity; spatial transcriptomics; biology ... See more keywords
SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes
Sign Up to like & getrecommendations! Published in 2021 at "Nucleic Acids Research"
DOI: 10.1093/nar/gkab043
Abstract: Abstract Spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute… read more here.
Keywords: nmf regression; cell; deconvolute; single cell ... See more keywords
Cell type identification in spatial transcriptomics data can be improved by leveraging cell-type-informative paired tissue images using a Bayesian probabilistic model
Sign Up to like & getrecommendations! Published in 2022 at "Nucleic Acids Research"
DOI: 10.1093/nar/gkac320
Abstract: Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited… read more here.
Keywords: cell; tissue images; transcriptomics data; tissue ... See more keywords
SPASCER: spatial transcriptomics annotation at single-cell resolution
Sign Up to like & getrecommendations! Published in 2022 at "Nucleic Acids Research"
DOI: 10.1093/nar/gkac889
Abstract: Abstract In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location and… read more here.
Keywords: cell; transcriptomics annotation; spatial transcriptomics; spascer spatial ... See more keywords
STellaris: a web server for accurate spatial mapping of single cells based on spatial transcriptomics data.
Sign Up to like & getrecommendations! Published in 2023 at "Nucleic acids research"
DOI: 10.1093/nar/gkad419
Abstract: Single-cell RNA sequencing (scRNA-seq) provides insights into gene expression heterogeneities in diverse cell types underlying homeostasis, development and pathological states. However, the loss of spatial information hinders its applications in deciphering spatially related features, such… read more here.
Keywords: cell; scrna seq; transcriptomics data; single cells ... See more keywords