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Method Article
A multistep computational procedure to identify candidate master Transcriptional Regulators (TRs) of glioblastoma (GBM)
Michelangelo Cordenonsi
Corresponding Author
Silvio Bicciato
Corresponding Author
Stefano Piccolo
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
We describe a multistep computational procedure to identify candidate master Transcriptional Regulators (TRs) of glioblastoma (GBM) from glioblastoma single cell gene expression profiles and tissue-specific transcription factors.
Keywords
gene regulatory network, master Transcriptional Regulators, single-cell RNA-seq analysis
This is a list of supplementary files associated with this preprint. Click to download.
- supplTable1.xlsx
Supplementary Table 1: List of candidate regulators for the network reverse engineering with ARACNe-AP as derived from analysis by the HOMER algorithm of the GBM ATAC-seq peaks of Corces et al. (2018)
- supplTable1.xlsx
Supplementary Table 1: List of candidate regulators for the network reverse engineering with ARACNe-AP as derived from analysis by the HOMER algorithm of the GBM ATAC-seq peaks of Corces et al. (2018)
- supplTable2.xlsx
Supplementary Table 2: mapping of each TR to a set of putative target genes as derived from Data S2 of Corces et al. (2018)
- supplTable2.xlsx
Supplementary Table 2: mapping of each TR to a set of putative target genes as derived from Data S2 of Corces et al. (2018)
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Associated Publications
Single-cell analyses reveal YAP/TAZ as regulators of stemness and cell plasticity in glioblastoma
by Martina Castellan, Alberto Guarnieri, Atsushi Fujimura, +14
Nature Cancer (07 December, 2020)
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This is a preprint. It has not completed peer review.
Method Article
A multistep computational procedure to identify candidate master Transcriptional Regulators (TRs) of glioblastoma (GBM)
Michelangelo Cordenonsi
Corresponding Author
Silvio Bicciato
Corresponding Author
Stefano Piccolo
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 09 Dec, 2020
No community comments so far
Metrics
Comments: 0
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
We describe a multistep computational procedure to identify candidate master Transcriptional Regulators (TRs) of glioblastoma (GBM) from glioblastoma single cell gene expression profiles and tissue-specific transcription factors.
Associated Publications
Single-cell analyses reveal YAP/TAZ as regulators of stemness and cell plasticity in glioblastoma
by Martina Castellan, Alberto Guarnieri, Atsushi Fujimura, +14
Nature Cancer (07 December, 2020)