Supporting data for "Massive NGS Data Analysis Reveals Hundreds Of Potential Novel Gene Fusions in Human Cell Lines"

Dataset type: Genomic
Data released on May 15, 2018

Gioiosa S; Bolis M; Flati T; Massini A; Garattini E; Chillemi G; Fratelli M; Castrignanò T (2018): Supporting data for "Massive NGS Data Analysis Reveals Hundreds Of Potential Novel Gene Fusions in Human Cell Lines" GigaScience Database.


Gene fusions derive from chromosomal rearrangements and the resulting chimeric transcripts are often endowed with oncogenic potential. Furthermore, they serve as diagnostic tools for the clinical classification of cancer subgroups with different prognosis and, in some cases, they can provide specific drug targets. So far, many efforts have been carried out to study gene fusion events occurring in tumor samples. In recent years, the availability of a comprehensive Next Generation Sequencing dataset for all the existing human tumor cell lines has provided the opportunity to further investigate these data in order to identify novel and still uncharacterized gene fusion events. In our work, we have extensively reanalyzed 935 paired-end RNA-seq experiments downloaded from "The Cancer Cell Line Encyclopedia" repository, aiming at addressing novel putative cell-line specific gene fusion events in human malignancies. The bioinformatics analysis has been performed by the execution of four different gene fusion detection algorithms. The results have been further prioritized by running a bayesian classifier which makes an in silico validation. The collection of fusion events supported by all of the predictive softwares results in a robust set of ~1,700 in-silico predicted novel candidates suitable for downstream analyses. Given the huge amount of data and information produced, computational results have been systematized in a database named LiGeA. The database can be browsed through a dynamical and interactive web portal, further integrated with validated data from other well known repositories. Taking advantage of the intuitive query forms, the users can easily access, navigate, filter and select the putative gene fusions for further validations and studies. They can also find suitable experimental models for a given fusion of interest. We believe that the LiGeA resource can represent not only the first compendium of both known and putative novel gene fusion events in the catalog of all of the human malignant cell lines, but it can also become a handy starting point for wet-lab biologists who wish to investigate novel cancer biomarkers and specific drug targets.

Additional details

Additional information:


Sample IDTaxonomic IDCommon NameGenbank NameScientific NameSample Attributes
CCLE_9319606HumanhumanHomo sapiens Description:Cell line from Liver hepatocellular ca...
Disease status:Liver hepatocellular carcinoma
Cell type:SNU869
CCLE_9329606HumanhumanHomo sapiens Description:Cell line from Colon adenocarcinoma SW...
Disease status:Colon adenocarcinoma
Cell type:SW403
CCLE_9339606HumanhumanHomo sapiens Description:Cell line from Colon adenocarcinoma CW...
Disease status:Colon adenocarcinoma
Cell type:CW2
CCLE_9349606HumanhumanHomo sapiens Description:Cell line from Lymphoid Neoplasm Diffu...
Disease status:Lymphoid Neoplasm Diffuse Large B-c...
Cell type:DOHH2
CCLE_9359606HumanhumanHomo sapiens Description:Cell line from Lung squamous cell carc...
Disease status:Lung squamous cell carcinoma
Cell type:NCIH441
Displaying 931-935 of 935 Sample(s).

File NameSample IDData TypeFile FormatSizeRelease Date 
Tabular DataTAR87.86 MB2018-04-30
GitHub archivearchive412.28 KB2018-04-30
ReadmeTEXT3.15 KB2018-04-30
Displaying 1-3 of 3 File(s).
Funding body Awardee Award ID Comments
Fondazione Italo Monzino Maddalena Fratelli 17058
ELIXIR-IIB Tiziano Flati 05/AR/2016-IBBE-BA Efficient allocation of HPC bioinformatics resources through a federation of Galaxy webbased infrastructures (Elixir-ITA project)
ELIXIR-IIB Silvia Gioiosa 08/AR/2016-IBBE-BA Efficient implemenation and distribution of HPC bioinformatics resources for Elixir scientific community (Elixir-ITA project)
Date Action
May 15, 2018 Dataset publish