CRISPR Coverage Calculator - Library Size & Tiling

Calculate CRISPR screen coverage, sgRNA library size, cell representation, oligo tiling overlap, redundancy, and gap risk. Use this coverage calculator before synthesis dropout, batch QC, or vendor-order formatting decisions.

CRISPR coverage and tiling library sizing workspace

Example input: 20,000 guides at 500x representation, or a 3 kb target tiled with 150 nt oligos and 30 nt overlap.

Read the result: complete coverage means no gaps; gap regions require tighter spacing, higher redundancy, or a different oligo length.

Next path: use Error Rate and Uniformity when dropout changes effective coverage, then Batch QC before ordering.

Input Parameters

Range: 10 bp - 10 Mbp. For genomes, enter the size of your target region.

Range: 10-500 nt. Typical: 150-200 nt for gene synthesis

Typical overlap: 20-50 bp (must be less than oligo length)

1 = single coverage, 2 = double coverage, etc. Higher redundancy increases reliability.

Understanding Coverage

  • • Tiling: Overlapping oligos assembled into longer sequences
  • • CRISPR: gRNAs distributed across target region for screening
  • • Redundancy: Multiple oligos covering the same region increases robustness
  • • Consider synthesis error rates when planning redundancy

Results

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Enter parameters and click"Calculate Coverage"

What Is Library Coverage in CRISPR Screens?

Use this CRISPR coverage and library-sizing calculator when you need to calculate screen representation, cell-number scale, guide coverage, or tiling-library size. Use error-rate, uniformity, CRISPR guide, and dilution pages when synthesis dropout, pool balance, or wet-lab preparation context is still the main decision.

Example input: a 20,000-guide CRISPR library at 500x representation, or a 3 kb target tiled with 150 nt oligos and 30 nt overlap. Interpret complete coverage as no gap regions; if gaps appear, reduce spacing, increase redundancy, or change oligo length before ordering.

Library coverage (also called representation or screen depth) is the average number of cells per guide RNA in a CRISPR screen. It determines whether you have enough statistical power to detect true hits. Inadequate coverage means that some guides will have too few cells for reliable phenotype measurement, leading to false negatives. The minimum recommended coverage is 200-500× for growth/viability screens and 500-1000× for more complex phenotypes.

Coverage calculation should account for pool non-uniformity: if some guides are underrepresented (for example, at 0.1× the mean abundance), effective coverage for those guides is much lower than average coverage. The calculator lets you enter expected uniformity from the Uniformity Estimator to estimate effective minimum coverage and required cell numbers.

For gene synthesis tiling applications, coverage refers to how many overlapping oligos span each region of the target sequence. Higher tiling redundancy can improve assembly robustness but requires more oligos and higher cost. The calculator estimates oligo placement needed to reach target coverage while keeping pool size visible.

How to Use the Coverage Calculator

  1. For CRISPR screens: enter library size (number of guides), desired coverage per guide, and pool uniformity (CV% or fold-difference). The calculator shows required cell numbers for transduction.
  2. For gene tiling: enter target sequence length, desired oligo length, and overlap size. The calculator shows number of oligos needed and coverage across the target.
  3. Adjust parameters to find the optimal balance between coverage, cost, and experimental feasibility.
  4. Review the coverage distribution chart to identify any gaps or regions with low coverage.
  5. Use the output to plan your experimental scale: cell culture volumes, sequencing depth for deconvolution, etc.

Frequently Asked Questions

What is the minimum coverage for a CRISPR screen?
For negative selection (dropout) screens: 200-500× coverage is standard. For positive selection screens: 100-200× may be sufficient since selected hits enrich strongly. For complex phenotypes (morphology, reporter-based): 500-1000× is recommended. These numbers refer to the initial representation at the time of library transduction — you also need to maintain coverage throughout the screen duration by passaging enough cells.
How do I calculate the number of cells needed for a CRISPR screen?
Total cells = library_size × desired_coverage × (1 / MOI) × (1 / min_fold_representation). For a 20,000-guide library at 500× coverage, MOI 0.3, and 5× fold-difference: cells = 20,000 × 500 × (1/0.3) × 5 = 167 million cells. The MOI factor accounts for the transduction efficiency, and the fold-difference factor accounts for pool non-uniformity.
What is MOI and how does it affect coverage?
Multiplicity of infection (MOI) is the ratio of virus particles to cells during lentiviral transduction. For CRISPR screens, MOI should be 0.3-0.5 to ensure most transduced cells receive only one guide RNA. At MOI 0.3, approximately 26% of cells are transduced (Poisson distribution). This means you need about 3-4× more total cells than the desired number of transduced cells.
How does oligo pool uniformity affect screen results?
Non-uniform pools mean some guides have lower effective coverage. If the worst-represented guides are at 0.1× the mean, their effective coverage is only 10% of the average. These underrepresented guides are more likely to generate noisy data or false negatives. Use the Uniformity Estimator to predict your pool distribution, then input the fold-difference into this calculator to compute adequate cell numbers.
What tiling overlap should I use for gene synthesis?
For Gibson assembly: 20-40 bp overlap is standard (25 bp recommended). For Golden Gate assembly: 4 bp overlaps at defined restriction sites. For capture arrays: 1-2× tiling with 50% oligo-length overlap. For mutagenesis scanning: 1 bp step size for saturation coverage. The calculator estimates oligo positions based on your specified overlap and target coverage.

Related Tools

Uniformity Estimator

Predict pool uniformity to estimate the fold-difference input for coverage calculation.

Batch Sequence QC

Validate your oligo pool sequences to minimize dropout and improve effective coverage.

Dilution Calculator

Calculate pool resuspension and transduction volumes for your screen.

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Related reading

Continue with the page or tool that matches the next decision in your experiment.

Oligo Pool GuideCRISPR Library GuideError Rate CalculatorBatch Sequence QCPre-Order Oligo Pool QCCoverage Method Reference