Regulatory compliant software for mutation analysis in clinical diagnostics
the software for high quality mutational analyses in cancer precision medicine
ALTOmate is an integrated software for mutation analysis in the cancer precision medicine workflow. Targeting solid tumor applications, ALTOmate is CE marked for in vitro diagnostics (IVD) based on next-generation sequencing data. ALTOmate produces an accurate, highly selective list of tumor-specific mutations in gene panel and exome data at a fast turnaround time.
Encapsulated in a Singularity container for instant deployment within your IT infrastructure, ALTOmate delives results out of the box without configuration or interruption of your routine work. As a diagnostic specialist, you can rely on reproducible results, based on deterministic, fast and assumption free statistics.
ALTOmate consists of proprietary algorithms for read-trimming, read-alignment and mutation calling, based on our patented pattern recognition metrics (PBR). The single executable can handle sequencing data from various platform providers. ALTOmate will report nucleotide substitutions, small insertions and deletions in an industry standard VCF file, together with an audit trail of the analysis and relevant quality control metrics.
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Publications and patents
Defining eligible patients for allele-selective chemotherapies targeting NAT2 in colorectal cancer
Rendo, V., Kundu, S., Rameika, N., Ljungström, V., Svensson, R., Palin, K., Aaltonen, L., Stoimenov, I., Sjöblom, T.
Scientific Reports, Volume 10 (1), 2020, December 31. doi:10.1038/s41598-020-80288-z
Somatic ephrin receptor mutations are associated with metastasis in primary colorectal cancer
Mathot, L., Kundu, S., Viktor Ljungström, V., Svedlund, J., Moens, L., Adlerteg, T., … Sjöblom T.
Cancer Research Volume 77 (7), 2017, April 1. doi: 10.1158/0008-5472.CAN-16-1921
A new distance measure for non-identical data with application to image classification
Swaminathan, M., Yadav, P., Piloto, O., Sjöblom T. and Cheong I.
Pattern Recognition, Volume 63, 2017, Mar 17. doi: 10.1016/j.patcog.2016.10.018
WO2016043659 – IMAGE RECOGNITION SYSTEM AND METHOD
Swaminathan, M., Sjöblom, T., Cheong, I. and Piloto, O.