SCOPIT

SCOPIT calculates sample-size probabilities for single-cell DNA and RNA sequencing experiments to determine the number of cells required to sample predefined counts from subpopulations such as specific cell types or cancer clones.

Key Features:

• Multinomial probability model: Computes the probability of sampling at least a predefined number of cells from each subpopulation using a multinomial distribution.
• Single-cell DNA and RNA support: Applies to both single-cell DNA sequencing and single-cell RNA sequencing experimental designs.
• Subpopulation-specific assessment: Evaluates sampling sufficiency for specified subpopulations, including specific cell types and cancer clones.
• Prospective and retrospective analysis: Enables both planning of required cell counts before experiments and evaluation of sampling sufficiency after sequencing.
• R package pmultinom: Provides the pmultinom R package for scripting, automation, and integration of probability calculations into workflows.

Scientific Applications:

• Experimental design and sample-size estimation: Determine the number of cells to sequence to achieve target probabilities of sampling subpopulations of interest.
• Retrospective evaluation of sequencing experiments: Assess whether an existing dataset contains sufficient cells from each subpopulation to support downstream analyses.
• Detection planning for rare cell types and cancer clones: Estimate required sampling depth to detect and characterize rare subpopulations or clones.
• Integration into analysis pipelines: Automate probability calculations within R-based bioinformatics workflows for batch or large-scale studies.

Methodology:

Performs probability calculations based on the multinomial distribution and implements these calculations in the R package pmultinom.