RNA-seq Data from 27 Glioblastoma Samples for XGBoost Modeling

RNA-seq data from 27 glioblastoma multiforme (GBM) samples, as published in the manuscript 'Topographic mapping of the glioblastoma proteome reveals a triple axis model of intra-tumoral heterogeneity' by Lam et al. The dataset is associated with research from the University of Toronto and is available under an Open Access license.

Use Cases

• Training XGBoost models to predict molecular subtypes based on RNA-seq expression profiles.
• Analyzing intra-tumoral heterogeneity in glioblastoma based on the described proteome mapping.
• Validating findings related to the triple axis model of tumor heterogeneity mentioned in the manuscript.

Strengths

• Data originates from a specific, peer-reviewed research manuscript.
• Focuses on 27 glioblastoma samples, providing a defined cohort for analysis.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Toronto, associated with the research of Brian Lam and co-authors.

Collection Method

RNA-seq data generated from 27 GBM samples, as described in the associated manuscript.