ArticleGenome research2016
INTEGRATE: gene fusion discovery using whole genome and transcriptome data.
Article in Genome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
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Who cites it
85 citing papers in PubMed.
- Characteristics of fusion genes in breast cancer.Cancer cell international · 2026Review
- MitoClipSplice: a machine learning framework for resolving mitochondrial RNA cleavage sites from strand-specific RNA-seq soft-clips.Briefings in bioinformatics · 2026Article
- A de novo assembly based fusion gene detection concept based on DNA-seq data of 100 Ewing sarcoma cases.Briefings in bioinformatics · 2026Article
- Clinical utility of targeted RNA sequencing in cancer molecular diagnostics.Nature medicine · 2025Article
- Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.Genomics, proteomics & bioinformatics · 2025Review
- Computational methods and data resources for predicting tumor neoantigens.Briefings in bioinformatics · 2025Review
- Strategies for neoantigen screening and immunogenicity validation in cancer immunotherapy (Review).International journal of oncology · 2025Review
- Architects and Partners: The Dual Roles of Non-coding RNAs in Gene Fusion Events.Methods in molecular biology (Clifton, N.J.) · 2025Article
- FGFR3-TACC3 fusion gene promotes glioblastoma malignant progression through the activation of STAT3 signaling pathway.Frontiers in oncology · 2025Article
- 3t-seq: automatic gene expression analysis of single-copy genes, transposable elements, and tRNAs from RNA-seq data.Briefings in bioinformatics · 2024Article
- Whole genome and reverse protein phase array landscapes of patient derived osteosarcoma xenograft models.Scientific reports · 2024Article
- Adenoid cystic carcinoma of the Bartholin's gland is underpinned by MYB- and MYBL1- rearrangements.Gynecologic oncology · 2024Article
- Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin.Cancer cell · 2023Article
- Article
- INTEGRATE-Circ and INTEGRATE-Vis: unbiased detection and visualization of fusion-derived circular RNA.Bioinformatics (Oxford, England) · 2023Article
- Detecting intragenic trans-splicing events from non-co-linearly spliced junctions by hybrid sequencing.Nucleic acids research · 2023Article
- Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival.Communications biology · 2023Article
- Ultrafast prediction of somatic structural variations by filtering out reads matched to pan-genome k-mer sets.Nature biomedical engineering · 2023Article
- Chimeric RNAiScience · 2023Article
- Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness.Cancer cell · 2023Article
25 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
Funding
Abstract
While next-generation sequencing (NGS) has become the primary technology for discovering gene fusions, we are still faced with the challenge of ensuring that causative mutations are not missed while minimizing false positives. Currently, there are many computational tools that predict structural variations (SV) and gene fusions using whole genome (WGS) and transcriptome sequencing (RNA-seq) data separately. However, as both WGS and RNA-seq have their limitations when used independently, we hypothesize that the orthogonal validation from integrating both data could generate a sensitive and specific approach for detecting high-confidence gene fusion predictions. Fortunately, decreasing NGS costs have resulted in a growing quantity of patients with both data available. Therefore, we developed a gene fusion discovery tool, INTEGRATE, that leverages both RNA-seq and WGS data to reconstruct gene fusion junctions and genomic breakpoints by split-read mapping. To evaluate INTEGRATE, we compared it with eight additional gene fusion discovery tools using the well-characterized breast cell line HCC1395 and peripheral blood lymphocytes derived from the same patient (HCC1395BL). The predictions subsequently underwent a targeted validation leading to the discovery of 131 novel fusions in addition to the seven previously reported fusions. Overall, INTEGRATE only missed six out of the 138 validated fusions and had the highest accuracy of the nine tools evaluated. Additionally, we applied INTEGRATE to 62 breast cancer patients from The Cancer Genome Atlas (TCGA) and found multiple recurrent gene fusions including a subset involving estrogen receptor. Taken together, INTEGRATE is a highly sensitive and accurate tool that is freely available for academic use.
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