Titre
An information theoretic approach to detecting spatially varying genes.
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Jones, D.C.
Auteure/Auteur
Danaher, P.
Auteure/Auteur
Kim, Y.
Auteure/Auteur
Beechem, J.M.
Auteure/Auteur
Gottardo, R.
Auteure/Auteur
Newell, E.W.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
2667-2375
Statut éditorial
Publié
Date de publication
2023-06-26
Volume
3
Numéro
6
Première page
100507
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Publication Status: epublish
Résumé
A key step in spatial transcriptomics is identifying genes with spatially varying expression patterns. We adopt an information theoretic perspective to this problem by equating the degree of spatial coherence with the Jensen-Shannon divergence between pairs of nearby cells and pairs of distant cells. To avoid the notoriously difficult problem of estimating information theoretic divergences, we use modern approximation techniques to implement a computationally efficient algorithm designed to scale with in situ spatial transcriptomics technologies. In addition to being highly scalable, we show that our method, which we call maximization of spatial information (Maxspin), improves accuracy across several spatial transcriptomics platforms and a variety of simulations when compared with a variety of state-of-the-art methods. To further demonstrate the method, we generated in situ spatial transcriptomics data in a renal cell carcinoma sample using the CosMx Spatial Molecular Imager and used Maxspin to reveal novel spatial patterns of tumor cell gene expression.
PID Serval
serval:BIB_3A146C47077F
PMID
Open Access
Oui
Date de création
2023-07-13T12:06:28.921Z
Date de création dans IRIS
2025-05-20T17:55:39Z
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Nom
37426750_BIB_3A146C47077F.pdf
Version du manuscrit
published
Licence
https://creativecommons.org/licenses/by/4.0
Taille
9 MB
Format
Adobe PDF
PID Serval
serval:BIB_3A146C47077F.P001
URN
urn:nbn:ch:serval-BIB_3A146C47077F9
Somme de contrôle
(MD5):3c0269b7930bce5dd73e6baf300c4060