oposSOM is a comprehensive data analysis software combining diversity analyses, biomarker selection, functional information mining, and visualization to the machine learning based ‘high-dimensional data portraying’.

The new oposSOM-Browser extends this toolkit and introduces the interactive browsing of single gene and function set profiles, of their mapping into the molecular ‘portrait landscape’, of phenotype diversity and associated survival differences, and of cellular signaling pathway activation patterns. Further, individual signature gene list can be mapped and evaluated regarding diagnostic quality.

Currently, oposSOM-Browser provides in-detail data analytics of five different data sets previously evaluated using oposSOM software, among them transcriptome of almost 1,000 lymphoma cases and healthy blood transcriptome of about 3,500 Leipzig inhabitants. Additional data sets and further functionalities are in the pipeline.




LYMPHOMA DATA SET (873 tumor samples, MMML consortium, LHA id 7WEWFE12CK-4)

MELANOMA DATA SET (80 tumor & nevi samples, Kunz et al., LHA id 7R4PDEM4HG-2)

LOWGRADE GLIOMA DATA SET (137 tumor samples, GGN consortium, LHA id 7Q0CFRJKW4-7)

GLIOMA GRADE 1-4 DATA SET (tumor samples, GGN consortium)

PNEUMONIA DATA SET (180 samples + 10 controls, Burnham et al., LHA id 7RU79AQTJD-9)

HEALTHY BLOOD TRANSCRIPTOM LIFE DATA SET (3388 samples, Schmidt et al., LHA id xxxxxxxxxxx)

BLOOD SAMPLES FROM CAR-T CELL THERAPY (77 meta-cells, Sheih et al. NatCom 2020)

METHYLOME OF LOW GRADE GLIOMA (122 tumor samples, GGN consortium, LHA id7YJY236M67-5)

COELIAC DISEASE (25 duodenal samples, Wolf et al., LHA id 86RMNYPQ1Q-0)