# Semi-parametric simulation tool for bulk and single-cell RNA sequencing data

## Documentation for package ‘SPsimSeq’ version 1.21.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

SPsimSeq-package | SPsimSeq package
buildXmat | An auxialiary function to quickly construct the polyomial matrix, using Horner's rule
calculateCPM | Calculates counts per millions of reads, possibly with log-transform
checkInputValidity | Check for data validity
chooseCandGenes | Select candidate genes
configExperiment | Configure experiment
constructDens | Construct the cumulative density
estLibSizeDistr | Estimate log-normal distribution for the library sizes
evaluateDensities | Evaluate the densities in the estimated SPsimSeq object
expit | Evaluate the expit function
extractMat | A function with S4 dispatching to extract the count matrix
extractMat-method | A function with S4 dispatching to extract the count matrix
fitLLmodel | Fit log linear model for each gene
fitPoisGlm | Fast fit Poisson regression
fracZeroLogitModel | Extract data and iterate over batches to estimate zero probability models
genCopula | Generate a copula instance
geneParmEst | Gene level param estimates for density estimation
genLibSizes | Generate library sizes from log-normal
matchCopula | Match copulas to estimated SP distribution
obtCorMatsBatch | A function to obtain copulas or uniform random variables
obtCount | Calculates height and mid points of a distribution
parmEstDensVec | Density estimation on a single vector
prepareSPsimOutputs | A function to prepare outputs
samZeroID | Return ID for observations to be set to zero
scNGP.data | Neuroblastoma NGP cells single-cell RNA-seq.
selectGenes | Sample genes from candidate genes
SPsimPerGene | A function that generates the simulated data for a single gene
SPsimSeq | A function to simulate bulk or single cell RNA sequencing data
zeroProbModel | Predict zero probability using logistic rgression
zhang.data.sub | Neuroblastoma bulk RNA-seq data retrieved from Zhang et (2015).