ArticleSTAR protocols2021
Integrative modeling identifies genetic ancestry-associated molecular correlates in human cancer.
Article in STAR protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- KnowYourCG: Facilitating base-level sparse methylome interpretation.Science advances · 2025Article
- Integrated systems biology reveals an 8-gene signature predicting early-stage lung adenocarcinoma progression and patient survival.Scientific reports · 2025Article
- Analysis of germline-driven ancestry-associated gene expression in cancers.STAR protocols · 2022Article
- DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse.Cell genomics · 2022Article
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Authors and funding
12 authors.
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Abstract
Cellular and molecular aberrations contribute to the disparity of human cancer incidence and etiology between ancestry groups. Multiomics profiling in The Cancer Genome Atlas (TCGA) allows for querying of the molecular underpinnings of ancestry-specific discrepancies in human cancer. Here, we provide a protocol for integrative associative analysis of ancestry with molecular correlates, including somatic mutations, DNA methylation, mRNA transcription, miRNA transcription, and pathway activity, using TCGA data. This protocol can be generalized to analyze other cancer cohorts and human diseases. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).
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