Home▸Molecular Biology▸Cell Hashing Demultiplexer 2D: HTO Scatter & Threshold Classifier

Cell Hashing Demultiplexer (2D)

Pool cells tagged with hashtag oligonucleotides (HTOs) into one 10x run, then watch a real k·sigma thresholding classifier separate singlets, doublets and negatives on a pannable 2D log-HTO scatter plot with a live per-channel histogram — tune the loading, ambient noise and threshold to see classification accuracy respond.

Molecular Biology2DAdvanced60 FPS📱 Mobile-adapted⇄ 3D version

Details

CategoryMolecular Biology

RenderingCanvas 2D

DifficultyAdvanced

Target FPS60

ControlsSliders adjust the number of cells loaded (Poisson droplet occupancy), ambient HTO background noise, and the classifier's k-sigma threshold; buttons resample a fresh pooled run, toggle the scatter view between the classifier's calls and the simulation's ground-truth labels, and reset the pan/zoom; drag the scatter panel to pan and scroll/pinch to zoom, and pick a channel button to switch which HTO's UMI histogram the side panel shows.

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Cell hashing lets a lab pool several samples into one single-cell sequencing run by tagging each sample's cells with a distinct hashtag oligo (HTO) before mixing them into the same microfluidic lane. This 2D simulator generates a realistic pool of cells under Poisson droplet-loading statistics, samples each cell's four-channel HTO UMI counts from signal-plus-ambient-noise distributions, and runs a real per-channel k·σ thresholding classifier to call every droplet a singlet (one sample), a doublet (two samples accidentally co-encapsulated), or a negative (no cell) — plotted on a pannable, zoomable log-HTO scatter with a live per-channel histogram of the fitted threshold. Adjust the loading concentration, ambient noise level and classifier threshold to see the trade-off between catching true doublets and over-calling noisy singlets as false doublets, with live accuracy measured against the simulation's own ground truth.

⚙ Under the hood

Pool cells from four samples tagged with hashtag oligonucleotides (HTOs) into one sequencing run, then watch a real per-channel k-sigma thresholding classifier separate singlets, doublets and negatives on a pannable, zoomable 2D log-HTO scatter plot with a live per-channel UMI histogram, with Poisson droplet-loading statistics and tunable ambient noise driving classification accuracy.

single-cellcell hashinggenomicscanvas 2ddoublet detectionmolecular biology

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install