# Oscope - A statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-seq

## Documentation for package ‘Oscope’ version 1.8.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Code demos. Use demo() to run them.
- Package NEWS.

## Help Pages

Oscope-package | Oscope - A statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-seq
AbsCor | Calculate absolute correlations among gene pairs
CalcMV | Calculate estimated mean and variance of RNA-Seq data
FlagCluster | Flag gene clusters with small within-cluster phase differences and/or small within-cluster sine scores
FormatSineOut | Format SinFun outputs from lists to matrix
ImpShift | Search for the optimal sample order by using the Extended Nearest Insertion
NISFun | Run Extended Nearest Insertion and 2-opt on a gene cluster identified by OscopeKM function
NormForSine | Rescale the gene/isoform expression matrix
Opt2Shift | Run the 2-opt algorithm to improve the optimal order searching of the Extended Nearest Insertion
Oscope | Oscope - A statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-seq
OscopeENI | Search for the optimal sample order for different gene clusters
OscopeExampleData | Simulated gene level data set with 600 genes and 30 cells.
OscopeKM | Oscope K medoid module
OscopeSine | Apply sine model on the full set of genes or isoforms
PermuCut | Define sine scroe cutoff using permuted data
PipeR | Calculate residual of polynomial fit
PipeShiftCDF | Calculate residual of the sliding polynomial regression
scanK | Run k-medoid algorithm with varying k on similarity matrix
SineFun | Apply sine model on one particular gene vs. other genes
SineOptim | Function for searching optimal phase shift