Quality Control in Sequencing Data: A Day in My Grad Student Life
Working with sequencing data is a lot like opening a mysterious treasure chest; there is the thrill of discovery, but also the risk that what is inside might not be as valuable as you hoped. Hidden within those files could be the genomic equivalent of gold or just a lot of noise. This is where Quality Control (QC) becomes indispensable. In my recent learning from NASA's Genelab On-demand course, we focused on S equencing data QC, the crucial first step before diving into analysis. No matter how advanced your downstream methods are, poor-quality input will always produce unreliable output. In bioinformatics, the saying “garbage in, garbage out” couldn’t be more true. Why QC Matters? When we get raw data from sequencing machines i.e. FASTQ files, it is not perfect. Errors creep in due to base-calling mistakes, adapter contamination, overrepresented sequences, or even leftover PCR duplicates. If we skip QC, we might spend hours or days analyzing flawed da...