SlideCNA: Spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data Article Swipe
Diane Zhang
,
Åsa Segerstolpe
,
Michal Slyper
,
Julia Waldman
,
Evan Murray
,
Ofir Cohen
,
Orr Ashenberg
,
Daniel L. Abravanel
,
Judit Jané‐Valbuena
,
Simon Mages
,
Ana Lako
,
Karla Helvie
,
Orit Rozenblatt–Rosen
,
Scott J. Rodig
,
Fei Chen
,
Nikhil Wagle
,
Aviv Regev
,
Johanna Klughammer
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.11.25.517982
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.11.25.517982
Solid tumors are spatially heterogeneous in their genetic, molecular and cellular composition, and this variation can be meaningful for diagnosis, prognosis and therapy. Recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we developed SlideCNA, a computational tool to extract sparse spatial CNA signals from spatial transcriptomics data, using expression-aware spatial binning. We test SlideCNA on simulated and real Slide-seq data of metastatic breast cancer (MBC) and demonstrate its potential for spatial sub-clone detection.
Related Topics
Concepts
Leverage (statistics)
Spatial analysis
Computational biology
Transcriptome
Copy-number variation
Computer science
Spatial variability
Biology
Bioinformatics
Artificial intelligence
Gene expression
Genome
Genetics
Gene
Mathematics
Statistics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2022.11.25.517982
- https://www.biorxiv.org/content/biorxiv/early/2022/11/27/2022.11.25.517982.full.pdf
- OA Status
- green
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4310272931
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4310272931Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2022.11.25.517982Digital Object Identifier
- Title
-
SlideCNA: Spatial copy number alteration detection from Slide-seq-like spatial transcriptomics dataWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-27Full publication date if available
- Authors
-
Diane Zhang, Åsa Segerstolpe, Michal Slyper, Julia Waldman, Evan Murray, Ofir Cohen, Orr Ashenberg, Daniel L. Abravanel, Judit Jané‐Valbuena, Simon Mages, Ana Lako, Karla Helvie, Orit Rozenblatt–Rosen, Scott J. Rodig, Fei Chen, Nikhil Wagle, Aviv Regev, Johanna KlughammerList of authors in order
- Landing page
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https://doi.org/10.1101/2022.11.25.517982Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2022/11/27/2022.11.25.517982.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2022/11/27/2022.11.25.517982.full.pdfDirect OA link when available
- Concepts
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Leverage (statistics), Spatial analysis, Computational biology, Transcriptome, Copy-number variation, Computer science, Spatial variability, Biology, Bioinformatics, Artificial intelligence, Gene expression, Genome, Genetics, Gene, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.spatial | 25, 59, 63, 68, 89 |
| abstract_inverted_index.studies | 27 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.SlideCNA | 72 |
| abstract_inverted_index.binning. | 69 |
| abstract_inverted_index.cellular | 11 |
| abstract_inverted_index.genetic, | 8 |
| abstract_inverted_index.identify | 45 |
| abstract_inverted_index.leverage | 39 |
| abstract_inverted_index.therapy. | 23 |
| abstract_inverted_index.Slide-seq | 77 |
| abstract_inverted_index.SlideCNA, | 52 |
| abstract_inverted_index.developed | 51 |
| abstract_inverted_index.molecular | 9 |
| abstract_inverted_index.potential | 41, 87 |
| abstract_inverted_index.profiling | 26 |
| abstract_inverted_index.prognosis | 21 |
| abstract_inverted_index.simulated | 74 |
| abstract_inverted_index.spatially | 4 |
| abstract_inverted_index.sub-clone | 90 |
| abstract_inverted_index.variation | 15, 34 |
| abstract_inverted_index.detection. | 91 |
| abstract_inverted_index.diagnosis, | 20 |
| abstract_inverted_index.meaningful | 18 |
| abstract_inverted_index.metastatic | 80 |
| abstract_inverted_index.alterations | 48 |
| abstract_inverted_index.demonstrate | 85 |
| abstract_inverted_index.separately. | 37 |
| abstract_inverted_index.composition, | 12 |
| abstract_inverted_index.computational | 54 |
| abstract_inverted_index.heterogeneous | 5 |
| abstract_inverted_index.transcriptomics | 64 |
| abstract_inverted_index.expression-aware | 67 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5091889636, https://openalex.org/A5068721624, https://openalex.org/A5004067604 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 18 |
| corresponding_institution_ids | https://openalex.org/I107606265, https://openalex.org/I4210117453, https://openalex.org/I63966007, https://openalex.org/I8204097 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.7900000214576721 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.46090314 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |