Free AI-Assisted

DistroGene Probability Calculator

Calculate CRISPR coverage, GO enrichment, variant depth, and barcode collision probabilities with reverse sizing and Methods export. Built-in AI agent assistant support.

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Key facts

Key facts about DistroGene Probability Calculator
FactValue
ScenariosCRISPR coverage, GO enrichment, variant detection, barcode collision, overdispersed counts, custom
DistributionsPoisson, hypergeometric, binomial, negative binomial
Sizing ModesForward (parameters → P) and Reverse (target P → required reads, cells, or depth)
Tail DirectionsP(X = k), P(X ≥ k), P(X > k), P(X ≤ k), P(X < k)
Organism PresetsHuman (~20k), Mouse (~20k), Fly (~14k), Worm (~20k), Yeast (~6k), Arabidopsis (~27k)
Advanced FactorsCRISPR 10× library skew, UMI GC base bias, sequencing error rate ε
Outputs & ExportP, E[X], σ, Fold Enrichment, curve (SVG/PNG), parameter CSV, Methods text
Runs in browserYes — client-side execution; no account required
AI assistantBuilt-in; fills scenario parameters, validates inputs, and interprets outputs

What it does

DistroGene Probability Calculator maps common genomics experimental setups—CRISPR library coverage, GO pathway enrichment, variant read depth, UMI barcode collisions, and overdispersed counts—to exact probability distributions. It replaces manual conversion of biological parameters into abstract math symbols by providing biological inputs, forward and reverse calculation modes, and publication-ready Methods text in your browser.

You enter biologically intuitive inputs such as library size, total reads per guide, target pathway gene count, query set size, or variant allele frequency. The calculator computes the exact tail probability P(X ≥ k), expected mean E[X], standard deviation σ, and fold enrichment ratio. An interactive probability curve displays 95% and 99% reference lines, allowing you to visually inspect coverage thresholds across varying sample sizes or sequencing depths.

The tool eliminates hand-calculating Poisson λ or hypergeometric factorials, preventing arithmetic errors caused by mismatched population sizes or incorrect tail directions. Optional advanced toggles let you account for real-world laboratory conditions like 10× CRISPR library representation skew, GC-biased UMI base composition, and sequencing background error rates (ε). Switching to Reverse Mode automatically solves for the minimum read depth or cell number needed to achieve your target probability.

Why researchers use it

  • Prevent coverage errors by mapping MOI directly to Poisson distribution probabilities
  • Compute hypergeometric enrichment p-values for population sizes up to N = 10¹⁰
  • Reverse-solve minimum sequencing depth needed for target 95% or 99% statistical confidence
  • Account for real-world CRISPR library skew and UMI base composition biases
  • Copy publication-ready Methods text detailing exact statistical distribution parameters and formulas
  • Export interactive probability curves as high-resolution SVG or 300 dpi publication PNGs

Best for

  • Planning pooled CRISPR or shRNA screen cell numbers and sequencing coverage per guide
  • Evaluating single gene-set or GO pathway overlap significance against organism population backgrounds
  • Estimating read depth required to detect low-frequency variant alleles above sequencing noise
  • Assessing UMI or sample index barcode collision risk prior to high-throughput multiplexing
  • Calculating overdispersed count tail probabilities using negative binomial mean and dispersion

When to use this vs alternatives

Choose DistroGene Probability Calculator when you need fast, biological-first probability estimates for single experimental scenarios without writing custom R code. If you need to analyze multi-list set intersections and pairwise overlap matrices across custom gene lists, use Smart List Overlap. For prospective continuous power analysis and sample-size curves across t-tests or ANOVA, use Power & Effect Navigator. To select the correct hypothesis test for observational data, consult Biostat Test Navigator.

What makes it different

Unlike generic statistical calculators that demand raw math inputs, or complex simulation packages that require uploading raw count files, DistroGene Probability Calculator delivers instant analytical solving with biological field labels. It bridges practical lab realities—such as library skew and barcode bias—with log-space precision for populations up to N = 10¹⁰.

Researchers switch to DistroGene Probability Calculator because it removes friction from routine experiment design. Instead of opening R or constructing manual 2x2 contingency tables, you select your biological scenario, adjust for real lab skew, and copy publication-ready Methods text in seconds—ensuring reproducible, mathematically sound screen design without coding overhead.

How to get started

  1. Select a Scenario Preset: Choose CRISPR Library Coverage, GO Enrichment, Variant Detection, Barcode Collision, Overdispersed Library, or Custom.
  2. Enter Biological Parameters: Input lab values or click Load Example to pre-fill a realistic worked setup.
  3. Set Direction & Presets: Choose your tail direction (P(X ≥ k), P(X = k), etc.) and select an organism population preset if testing enrichment.
  4. Configure Advanced Options (Optional): Toggle library skew, UMI base bias, or sequencing error rate to adjust for lab conditions.
  5. Calculate & Export: Click Calculate to view results, inspect the probability curve, and copy Methods text or export a summary CSV.

Frequently asked questions

Which probability distribution does each scenario preset use?
CRISPR library coverage uses the Poisson distribution (λ = reads per guide). GO pathway enrichment uses the hypergeometric distribution. Variant detection uses the binomial distribution adjusted for error rate ε. Barcode collision uses the birthday Poisson approximation. Overdispersed count data uses the negative binomial distribution specified by mean μ and dispersion r.
How does the calculator handle large population sizes for GO enrichment?
Hypergeometric calculations employ log-space factorial arithmetic to compute exact combinations without numerical overflow. This enables reliable p-value calculation for background population sizes up to N = 10¹⁰ (such as whole human genome or transcriptome backgrounds). An informational badge alerts you when log-space arithmetic is active.
What does Reverse Mode solve for in experiment design?
Reverse Mode binary-searches the primary sizing variable to meet your specified target probability (such as 0.95 or 0.99). Depending on the selected scenario, it calculates the required reads per guide, total sequencing depth, query set size, or cell numbers needed to achieve your desired statistical coverage confidence.
How do advanced lab adjustments like library skew affect coverage math?
Uniform distribution models assume equal guide or barcode representation, which overestimates coverage in real experiments. Enabling 10× library skew evaluates representation for low-abundance guides at the 10th percentile. Similarly, UMI base composition bias adjusts the effective barcode space B_eff = 4^(L · H_eff) to reflect GC content imbalances.
Can I export figures and Methods text for my publication?
Yes. Clicking Copy Methods text generates auto-formatted methodology prose detailing the chosen distribution, parameters, and tail direction. You can also download the interactive probability curve as a vector SVG or 300 dpi PNG formatted with publication-safe Arial typography, colorblind-friendly lines, and transparent backgrounds for manuscript preparation.
Can I use an AI agent or MCP with DistroGene Probability Calculator?
Yes. The workspace includes a built-in assistant that helps configure scenario parameters and interpret warnings. For external automated workflows in Cursor, OpenClaw, or custom scripts, the tool is exposed via [API & MCP](/tools/developers) under the tool name pepkio_distrogene-probability-calculator.

Client source code & registry

Last updated . Pepkio builds free lab calculators alongside bioinformatics CRO services.