Question 15 of 20 Intermediate Practical
How would you estimate library complexity and decide whether deeper sequencing is worthwhile?
Short answer
Estimate how many distinct molecules the library holds, from duplicate rates or a complexity curve such as preseq's, and project how many new molecules more reads would add. If the curve has flattened, more sequencing mostly returns duplicates and a new library is the better buy.
Why
Library complexity is the number of distinct original molecules available to sequence. Daley and Smith define the complexity curve as the expected number of distinct molecules seen as a function of reads sequenced, and show it can be extrapolated from a shallow run. Their warning is that early curves can mislead: two libraries can look linear at 5 million reads and then cross, so a naive comparison picks the wrong one.
Picard reports PERCENT_DUPLICATION and an ESTIMATED_LIBRARY_SIZE in unique molecules, based on paired-end duplication. When a library is low in complexity, the preseq authors note that deeper sequencing either gives redundant data that is discarded or introduces bias. So the decision is economic and statistical.
If projections show 20 percent more unique molecules for doubling the reads, resequencing is poor value. If the curve is still rising steeply, more reads pay. Duplicates have more than one origin.
Some come from PCR, some are optical duplicates from the instrument, and in high-coverage targeted or RNA-seq data many identical start sites arise naturally from abundant molecules.
How to work it through
- Mark duplicates and read the duplication rate and estimated library size.
- Run a complexity extrapolation on the aligned reads from the current run.
- Compare the projected distinct molecules at the planned depth with the number needed for the study.
- Check whether duplication is concentrated in a few regions, which suggests biology or capture bias rather than low complexity.
- Decide between resequencing the same library and preparing a new one with more input or fewer PCR cycles.
- Record the projection used to make the decision.
An example
A whole-genome library sequenced to 100 million read pairs shows 38 percent duplication and an estimated library size of 210 million molecules. The complexity curve projects that doubling to 200 million pairs would add only 45 million new distinct pairs. The team prepares a second library from more input DNA with four fewer PCR cycles, and the new library reaches 18 percent duplication at the same depth.
Where the answer stops holding
Extrapolation from very shallow data is uncertain, and estimates assume the next sequencing samples the same library. Natural duplicates in RNA-seq or amplicon data inflate apparent duplication without meaning low complexity. Estimated library size from duplication assumes paired reads and random fragmentation.
A strong answer covers
- Complexity is the number of distinct original molecules
- Complexity curves project returns from extra reads
- Early curves can cross, so shallow comparisons mislead
- Separate PCR, optical and natural duplicates
- Decide between resequencing and a new library
Common mistakes
- Ordering more reads from a saturated library
- Treating every duplicate in RNA-seq as a PCR artifact
- Comparing libraries on duplication rates measured at different depths
The interviewer might ask next
How do unique molecular identifiers change how you estimate complexity?