Which method uses depth-of-coverage analysis in sequencing to detect copy number variations?

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Multiple Choice

Which method uses depth-of-coverage analysis in sequencing to detect copy number variations?

Explanation:
Depth-of-coverage analysis detects copy-number variations by looking at how many sequencing reads map to each genomic region. If a region is duplicated, more copies produce more reads mapping there; if deleted, fewer reads map there. By comparing the observed read depth to an expected baseline (and adjusting for factors like GC content and mappability), you can call gains or losses across the genome. This approach is directly tied to sequencing data and can detect CNVs genome-wide, across a wide range of sizes. Karyotyping visualizes chromosomes to find large-scale changes but misses smaller CNVs. Sanger sequencing targets a single gene and isn’t suited for genome-wide copy-number assessment. FISH can detect some CNVs at specific loci but is targeted and limited by probe design and resolution.

Depth-of-coverage analysis detects copy-number variations by looking at how many sequencing reads map to each genomic region. If a region is duplicated, more copies produce more reads mapping there; if deleted, fewer reads map there. By comparing the observed read depth to an expected baseline (and adjusting for factors like GC content and mappability), you can call gains or losses across the genome. This approach is directly tied to sequencing data and can detect CNVs genome-wide, across a wide range of sizes. Karyotyping visualizes chromosomes to find large-scale changes but misses smaller CNVs. Sanger sequencing targets a single gene and isn’t suited for genome-wide copy-number assessment. FISH can detect some CNVs at specific loci but is targeted and limited by probe design and resolution.

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