The　de　v　elopment　of　spatial　transcriptome　sequencing　technology　has　re　v　olutioniz　ed　our　comprehension　of　complex　tissues　and　propelled　life　and　health　sciences　into　an　era　of　spatial　omics.　Ho　w　e　v　er,　the　current　a　v　ailability　of　databases　for　accessing　and　analyzing　spatial　transcriptomic　data　is　limited.　In　response,　w　e　ha　v　e　established　CR　OS　T　(　https://　ngdc.cncb.ac.cn/　crost　),　a　comprehensive　repository　of　spatial　transcriptomics.　CR　OS　T　encompasses　high-quality　samples　and　houses　182　spatial　transcriptomic　datasets　from　diverse　species,　organs,　and　diseases,　compris-　ing　1033　sub-datasets　and　48　043　tumor-related　spatially　variable　genes　(SVGs).　Additionally,　it　encompasses　a　standardized　spatial　transcriptome　data　processing　pipeline,　integrates　single-cell　RNA　sequencing　decon　v　olution　spatial　transcriptomics　data,　and　e　v　aluates　correlation,　colocal-　ization,　intercellular　communication,　and　biological　function　annotation　analy　ses.　Moreo　v　er,　CR　OS　T　integrates　the　transcriptome,　epigenome,　and　genome　to　explore　tumor-associated　SVGs　and　provides　a　comprehensive　understanding　of　their　roles　in　cancer　progression　and　prognosis.　Furthermore,　CR　OS　T　pro　vides　tw　o　online　tools,　single-sample　gene　set　enrichment　analy　sis　and　SpatialAP,　f　or　users　to　annotate　and　analyze　the　uploaded　spatial　transcriptomics　data.　The　user-friendly　interface　of　CROST　facilit　ates　browsing　,　searching　,　analyzing　,　visualizing　,　and　download-　ing　desired　inf　ormation.　Collectiv　ely,　CR　OS　T　offers　fresh　and　comprehensiv　e　insights　into　tissue　str　uct　ure　and　a　f　oundation　f　or　understanding　multiple　biological　mechanisms　in　diseases,　particularly　in　tumor　tissues.　©　The　Author(s)　2023.