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| Format: | Recurso digital |
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Zenodo
2022
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| Online Access: | https://doi.org/10.5281/zenodo.19665269 |
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Table of Contents:
- <p>Introduction Cancer is the leading cause of death worldwide, accounting for nearly 10 million<br>fatalities in 2020. Ovarian cancer, is the deadliest form of gynaecological malignancy, with<br>around 225,500 new cases diagnosed annually and 140,200 patients losing their life. The<br>extension of Hallmarks of Cancer with further hallmarks, such as unlocking phenotypic<br>plasticity highlights the importance of New Generation Sequencing (NGS) for understanding<br>better the relationship between genes and cancer subtypes. NGS generates large and often<br>changing datasets that are difficult to store, organise and interpret, thus a flexible database is<br>required to allow fast and easy interaction with the datasets.</p> <p>Methodology To store metadata of gene counts and its BAM and FASTQ files along with the</p> <p>gene count tables, meta data and results of differential analysis and metadata of ChIP-<br>sequencing along with its BAM and FASTQ files and peak count tables, MongoDB has been</p> <p>identified as a potential database. Using Node.js allows faster interactions with the database<br>and MongoDB Query Language can be used to perform simple queries.</p> <p>Results A database have been developed in MongoDB which stores the required datasets in an<br>organised way. Scripts have been written to speed up the putting data into the database and to<br>perform complex queries. Queries have been written using MQL to access data stored in the<br>database. The database and the queries/scripts are functioning thus biological questions can be<br>answered.</p> <p>Discussion Due to its high flexibility, the database is easily can be expanded and new datasets.<br>The database can be used to understand drugs’ mechanism of action in different cancer<br>subtypes and to identify which genes could be responsible for developing resistance. The<br>database could be used to design subtype specific treatments, and after further development it<br>can be available for medical professionals providing a more accessible personalised medicine<br>approach.</p> <p>Keywords: ovarian cancer, New Generation Sequencing, RNA-sequencing, ChIP-<br>sequencing, MongoDB</p>