Assessing the quality of genomic data in Genelabs involves several essential metrics. One key metric is the read depth or coverage, which indicates the number of times a nucleotide is read during sequencing. Higher coverage generally leads to more accurate variant detection. Another important metric is the base quality score, which reflects the probability that a given base call is incorrect. Metrics such as the percentage of mapped reads and the rate of duplicate reads are also crucial for evaluating data quality. The percentage of GC content can provide insights into the amplification bias during sequencing. Additionally, variant quality score recalibration (VQSR) helps assess the accuracy of variant calling. Implementing these metrics in quality control processes ensures the reliability and accuracy of genomic data.
Key Takeaway: Read depth, base quality, and mapping metrics are essential for assessing genomic data quality in Genelabs.