Fits the modified Michaelis-Menten equation (MM), a logistic regession (logistic), or a double exponential (ZIFA) function to the relationship between mean expression and dropout-rate (proportion of zero values).
a numeric matrix of normalized (not log-transformed) expression values, columns = samples, rows = genes.
limits for x-axis of plot.
logical, whether to plot fit curves or not.
Plots the dropout-rate (P) vs average gene expression (S) for all genes. Fits three different models and adds the fitted curves to the plot. The three models are: MMfit : the Michaelis-Menten function
P = 1 - S/(K+S)
(see: ). LogiFit : a logistic regression between P and log base 10 of S (used by ). ExpoFit : a double exponential
P = e^(-lambda*S^2)
(used by ).
Invisibly, a list of output from each fit (MMfit, LogiFit, ExpoFit).
 Keener, J.; Sneyd, J. (2008). Mathematical Physiology: I: Cellular Physiology (2 ed.). Springer. ISBN 978-0-387-75846-6  Kharchenko, PV; Silberstein, L; Scadden, DT. (2014) Bayesian approach to single-cell differential expression analysis. Nature Methods. 11:740-742  Pierson, E; Yau, C. (2015) ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis. Genome Biology. 16:241 doi:10.1186/s13059-015-0805-z
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