There are numerous online databases dedicated to genes associated with human diseases. The redundancy and lack of consistency of disease terms in these databases pose a significant impediment in high throughput data analysis. To address this, we developed GeDiPNet by compiling data available on gene-disease associations from six popular open access sources namely DisGeNET, ClinGen, ClinVar, HPO, OrphaNet, and PsyGeNET; and curated through several stages including manual curation and merging of disease names to ensure standard vocabulary (Supplementary file 1). GeDiPNet currently includes information on 12,270 genes that have disease association curated from literature records and 20,013 genes have disease association based on text mining.