Chanjo : Clincal grade sequence coverage analysis

Coverage analysis is essential when analysing massive parallel sequencing (MPS) data. The analysis indicates existence of false negatives or positives in a region of interest or poorly covered genomic regions. There are several tools that have excellent performance when doing coverage analysis on a few samples with predefined regions. However, there is no current tool for collecting samples over a longer period of time for aggregated coverage analysis of multiple samples or sequencing methods. Furthermore, current coverage analysis tools do not generate customized coverage reports or enable exploratory coverage analysis without extensive bioinformatic skill and access to the original alignment files. We present Chanjo, a user friendly coverage analysis tool for persistent storage of coverage data, that, accompanied with Chanjo Report, produces coverage reports that summarize coverage data for predefined regions in an elegant manner. Chanjo Report can produce both structured coverage reports and dynamic reports tailored to a subset of genomic regions, coverage cut-offs or samples. Chanjo stores data in an SQL database where thousands of samples can be added over time, which allows for aggregate queries to discover problematic regions. Chanjo is well tested, supports whole exome and genome sequencing, and follows common UNIX standards, allowing for easy integration into existing pipelines. Chanjo is easy to install and operate, and provides a solution for persistent coverage analysis and clinical-grade reporting. It makes it easy to set up a local database and automate the addition of multiple samples and report generation. To our knowledge there is no other tool with matching capabilities. Chanjo handles the common file formats in genetics, such as BED and BAM, and makes it easy to produce PDF coverage reports that are highly valuable for individuals with limited bioinformatic expertise. We believe Chanjo to be a vital tool for clinicians and researchers performing M
QC 20230718