Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data
Identifying enriched gene sets in transcriptomic data is routine analysis. Here, the authors show that conventional gene category enrichment analysis (GCEA) applied to brain-wide atlas data yields biased results and develop a flexible ensemble-based null model framework to enable appropriate inferen...
Guardado en:
Autores principales: | Ben D. Fulcher, Aurina Arnatkeviciute, Alex Fornito |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a043385931fd4415a4b3a9fa307ff145 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain
por: Anoushka Joglekar, et al.
Publicado: (2021) -
Resolving resolution dimensions in triangulated categories
por: Ma Xin, et al.
Publicado: (2021) -
Spatially and cell-type resolved quantitative proteomic atlas of healthy human skin
por: Beatrice Dyring-Andersen, et al.
Publicado: (2020) -
Computational challenges and opportunities in spatially resolved transcriptomic data analysis
por: Lyla Atta, et al.
Publicado: (2021) -
Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface
por: Miranda V. Hunter, et al.
Publicado: (2021)