| Criteria | Sanger Sequencing | Next-Generation Sequencing (NGS) | Remarks |
| Definition | A first-generation DNA sequencing method based on selective incorporation of chain-terminating dideoxynucleotides (ddNTPs). | A group of high-throughput sequencing technologies that allow massively parallel sequencing of millions of DNA fragments simultaneously. | Sanger is traditional and low-throughput; NGS is modern and high-throughput. |
| Throughput | Low throughput; sequences one fragment at a time (up to ~1 kb). | High throughput; can sequence millions of fragments in parallel. | NGS is better for large-scale projects like whole-genome sequencing. |
| Read Length | Long reads (~500–1000 bp). | Shorter reads (~50–300 bp, depending on platform). | Sanger provides longer reads, useful for resolving repeats; NGS compensates with coverage. |
| Accuracy | High accuracy per read (~99.99%). | High accuracy with depth; errors can be reduced by sequencing coverage. | Sanger more accurate for single fragments; NGS excels in large datasets. |
| Time and Efficiency | Slower; requires gel or capillary electrophoresis. | Much faster; parallel processing enables rapid sequencing of entire genomes. | NGS revolutionized speed and efficiency. |
| Cost | More expensive per base but cheaper for small-scale sequencing (single genes, plasmids). | Cheaper per base but higher startup costs for instruments. | Choice depends on project size and budget. |
| Applications | Useful for small projects: sequencing plasmids, PCR products, and verifying constructs. | Suitable for large projects: genome sequencing, transcriptomics, epigenomics, metagenomics. | Sanger remains in use for validation; NGS dominates large-scale research. |
| Scalability | Not scalable for large genomes or populations. | Highly scalable for massive datasets. | NGS is essential for population and systems biology studies. |
