Software Packages

Department of Quantitative Health Sciences
Mayo Clinic Research
Formerly known as the Department of Health Sciences Research

Related links: Division Overview R Shiny Applications


A bioinformatics tool to identify fusion transcripts from paired-end transcriptome sequencing data. The tool employs multiple steps of false positive filtering and nominates the fusion candidates with high confidence (approaching 100% true positive rate). The unique features of SnowShoes-FTD include: (i) the ability to discover multiple fusion isoforms in which the two gene partners give rise to transcripts with different junctions; (ii) prediction of potential fusion mechanisms including inversion, translocation, and/or interstitial deletions; (iii) identification of whether the junction point in a fusion transcript occurs at the boundaries of known exons which implies the fusion events might have happened inside an intron in DNA and transcribed to the fusion transcript.

Furthermore, the SnowShoes-FTD greatly simplifies the validation process of the fusion candidates by giving a 5’ to 3’ oriented template region spanning fusion junction point which is long enough for designing primers for PCR validation of the fusion candidates. The SnowShoes-FTD also predicts the protein sequences of the fusion genes using known transcript sequences of fusion partners and identifies in-frame vs. out-of-frame fusion products. In addition, the mutations including non-synonymous single amino acid changes and insertions at the fusion junction points for the in-frame fusion proteins are identified. The source codes of SnowShoes-FTD are provided in two formats: one configured to run on the Sun Grid Engine for parallelization with shorter run time, and the other formatted to run on a single LINUX node.

Note: The download package of the SnowShoes-FTD contains the tool itself, the reference files necessary to run the tool, and the test data. Because of its large size, we will set up a FTP transfer site for each request. We apologize for the inconvenience and we are looking for alternative sites to host the download.

Authors: Yan W. Asmann, Asif Hossain, Brian M. Necela, Sumit Middha, Krishna R. Kalari, Zhifu Sun, H.S. Chai, D.W. Williamson, Derek C. Radisky, G.P. Schroth, Jean-Pierre A. Kocher, Edith A. Perez, E. Aubrey Thompson

Publication: A novel bioinformatics pipeline for identification and characterization of fusion transcripts in breast cancer and normal cell lines

Please contact the author to gain access to the software:

Yan W. Asmann, Ph.D.

Page last modified: July 13, 2015