Library Complexity
Measure duplicate fraction and library complexity from distinct fragments.
Description
Distinct-fragment share is an observed library complexity summary.
Distinct-fragment share is an observed library complexity summary. It differs from extrapolating how many unseen molecules further sequencing might reveal.1
Measure duplicate fraction and library complexity from distinct fragments.
When to use Library Complexity
Use this tool to measure duplicate fraction and library complexity from distinct fragments.
Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.
How to use Library Complexity and understand its results
- Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.
- Enter totalMappedReads, distinctFragments using the field table and calculation rules, then run the tool.
- Read duplicatePercent, uniquePercent, readsPerFragment. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| totalMappedReads | Total mapped reads | number | Required |
| distinctFragments | Distinct fragments | number | Required |
Provide positive distinct-fragment and total mapped-read values, with distinct no greater than total. Calculate unique and duplicate percentages and average reads per distinct fragment. Equal counts give zero duplicates and one read per fragment.
unique%=100 distinct/total; duplicate%=100(total−distinct)/total; readsPerFragment=total/distinct Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| duplicatePercent | Duplicate percent | number |
| uniquePercent | Unique percent | number |
| readsPerFragment | Reads per fragment | number |
{
"input": {
"totalMappedReads": 100,
"distinctFragments": 80
},
"output": {
"duplicatePercent": 20,
"uniquePercent": 80,
"readsPerFragment": 1.25
}
}Limitations and assumptions
Counting units must be comparable, especially for paired-end data. No deduplication or saturation model is run, and zero distinct fragments are rejected rather than assigned a finite ratio.
Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Multimapper Fraction: Measure ambiguous multi-mapper assignment share. For a complementary task, use Insert Size Mode: Find the modal insert size, breaking ties toward the shorter fragment.
References
-
Library Complexity — tool.io
Similar or alternative tools
- Multimapper Fraction
Measure ambiguous multi-mapper assignment share.
- Insert Size Mode
Find the modal insert size, breaking ties toward the shorter fragment.