ArticleNucleic acids research2016
FocalScan: Scanning for altered genes in cancer based on coordinated DNA and RNA change.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
3 citing papers in PubMed.
- Structural Homology Fails to Predict Secretion Efficiency inInternational journal of molecular sciences · 2025Article
- CiberAMP: AnBiology · 2022Article
- A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Somatic genomic copy-number alterations can lead to transcriptional activation or inactivation of tumor driver or suppressor genes, contributing to the malignant properties of cancer cells. Selection for such events may manifest as recurrent amplifications or deletions of size-limited (focal) regions. While methods have been developed to identify such focal regions, finding the exact targeted genes remains a challenge. Algorithms are also available that integrate copy number and RNA expression data, to aid in identifying individual targeted genes, but specificity is lacking. Here, we describe FocalScan, a tool designed to simultaneously uncover patterns of focal copy number alteration and coordinated expression change, thus combining both principles. The method outputs a ranking of tentative cancer drivers or suppressors. FocalScan works with RNA-seq data, and unlike other tools it can scan the genome unaided by a gene annotation, enabling identification of novel putatively functional elements including lncRNAs. Application on a breast cancer data set suggests considerably better performance than other DNA/RNA integration tools.
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