Identify Pattern for Pseudo Temporal Cell Ordering

1 2 | ```
pseudotimepattern(expr, pseudotime, simplify = T, removeconstant = F,
plot = F, gap = 10)
``` |

`expr` |
The matrix of gene expression profile. |

`pseudotime` |
A character data.frame or matrix of pseudo-time. First column: Cell name; Second column: pseudo-time. |

`simplify` |
Whether to simplify pattern so that same neiboring patterns will be reduced to one. For example "up_up_constant" will be simplied to "up_constant". |

`removeconstant` |
Whether to remove all constant patterns. For example "up_up_constant" will be simplied to "up_up". This step will be performed before simplify. |

`plot` |
Whether to generate plot for genes with transition points. |

`gap` |
Number of first and last gap cells that will be excluded when considering transition points. |

Identify the gene expression patterns for true experiment time. For the expressions of each gene, the function performs t-tests for cells from neighboring time points. The expression pattern for cells from neiboring time points could be increasing, decreasing or constant. All patterns are concatenated using "-" to form the final pattern.

A list. expr: original expression matrix; pseudotime: original pseudotime; pattern: a list containing results of different patterns. For single patterns, it is a named vector where values are the p-values of the t-test of the simple linear regression slope coefficient. The vector is ordered according to the p-values. For transition patterns, a data.frame containing the mean and confidence interval of the transition point. It is ordered according to the transition points; fitexpr: the fitted expression matrix

Zhicheng Ji, Hongkai Ji <zji4@zji4.edu>

1 2 |

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