Peer Review Report For: Pharmosome: an integrative and collective database for exploration and analysis of single nucleotide polymorphisms associated with disease [version 1; peer review: 2 approved with reservations]

Current single nucleotide polymorphism (SNP) databases are limited to a narrow set of SNPs, which has led to a lack of interactivity between different databases, limited tools to analyze and manipulate the already existing data, and complexity in the graphical user interface. Here we introduce Pharmosome, a web-based, user-friendly and collective database for more than 30,000 human disease-related SNPs, with dynamic pipelines to explore SNPs associated with disease development, drug response and the pathways shared between different genes related to these SNPs. Pharmosome implements several tools to design primers to detect SNPs in large genomes and facilitates analysis of different SNPs to determine relationships between them by aligning sequences, constructing phylogenetic trees, and providing consensus sequences illustrating the connections between SNPs. Pharmosome was written in the Python programming language using the Django web framework in combination with HTML, CSS, and JavaScript to receive user inputs, and process and export the sorted result to the interface. Pharmosome is available from: https://pharmosome.herokuapp.com/ .