Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
LCP
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"
Image for the paper "Characterizing contaminant noise in barcoded perturbation experiments"

Cell soup in screens

Synthetic biology

Bursting cells can introduce noise in transcription factor screens, but modelling this process allows us to discern true counts from false.

Characterizing contaminant noise in barcoded perturbation experiments

Submitted (2023)

F. Sheldon

In a screening experiment, genes are transduced into cells to determine their effects. Transduced cells can burst, spilling their contents into the surrounding media. As a result, sequenced droplets can contain RNA-sequences from other cells, complicating efforts to identify transduced factors. This paper develops a systematic approach to this problem by (1) deriving an exact form for the distribution of observed noise counts assuming that they are the result of cells bursting and mixing through a large volume, and (2) applying this distribution to label cells with their transduced genes. Experiments support that all exogenous genes can be described by a single noise model with shared parameters. The labeled cells can then be translated into better understanding of genes' effects on cell type and function.

Submitted (2023)

F. Sheldon