Introduction to NGS Data Analysis

The Revolution of NGS

Next-Generation Sequencing (NGS) has transformed biology. Unlike Sanger sequencing, which processes one DNA fragment at a time, NGS processes millions of fragments in parallel. This massive throughput has dropped the cost of sequencing a human genome from $100M to under $200.

The Standard Workflow

1. Quality Control (QC): Raw data (FASTQ) must be checked for quality issues using tools like FastQC.
2. Trimming: Removing adapters and low-quality bases with Trimmomatic or fastp.
3. Alignment: Mapping reads to a reference genome. For DNA, we use BWA or Bowtie2. For RNA, splice-aware aligners like STAR are required.
4. Variant Calling / Quantification: Depending on the goal, we identify mutations (GATK) or count gene expression (featureCounts).

Challenges

Data storage and computational power are major bottlenecks. A single human genome can be 100GB. Efficient algorithms and cloud computing are becoming essential skills for bioinformaticians.