Utilising the IMMUcan database for meta- assessment of human cancer single-Cell RNA-seq databases

• Author Details:   
• Tshetiz Dahal ^*
• Suyash Saurabh

Understanding the tumour microenvironment (TME) has been made possible in large part by the advancement of single-cell RNA sequencing (scRNA-seq) technology. Numerous independent scRNA-seq studies have been published, which is a great resource that offers chances for meta-analysis research. However, there are significant barriers to fully utilising scRNA-seq data due to the vast amount of biological information, the notable diversity and heterogeneity within studies, and the technical difficulties in processing diverse datasets. We created IMMUcan scDB, a fully integrated scRNA-seq database that is open to nonspecialists and solely focused on human cancer. The 144 datasets on 56 distinct cancer types in the IMMUcan scDB are annotated in 50 domains with detailed biological, clinical, and technological data. Four steps comprised the development and organization of a data processing pipeline: (i) data collection; (ii) data processing (including sample integration and quality control); (iii) supervised cell annotation using a TME cell ontology classifier; and (iv) an interface to analyse TME globally or in relation to a particular cancer type. This framework was utilized to do meta-analysis research, such as rating immune cell types and genes linked to malignant transformation, and to investigate datasets across tumour locations in a gene-centric (CXCL13) and cell-centric (B cells) manner. An unparalleled degree of thorough annotation is provided by this integrated, publicly available, and user-friendly resource, which opens up a plethora of opportunities for the downstream exploitation of human cancer scRNA-seq data for discovery and validation investigations.