# Express function to carry out XBSeq analysis

### Description

A wrapper function to carry out XBSeq analysis procedure

### Usage

1 2 | ```
XBSeq(counts, bgcounts, conditions, method = "pooled",
sharingMode = "maximum", fitType = "local", pvals_only = FALSE, paraMethod='NP', big_count = 900)
``` |

### Arguments

`counts` |
A data.frame or matrix contains the observed signal |

`bgcounts` |
A data.frame or matrix contains the background noise |

`conditions` |
A factor to specify the experimental design |

`method` |
Method used to estimate SCV |

`sharingMode` |
Mode of sharing of information |

`fitType` |
Option to fit mean-SCV relation |

`pvals_only` |
Logical; Specify whether to extract pvalues only |

`paraMethod` |
Method to use for estimation of distribution parameters, 'NP' or 'MLE'. See details section for details |

`big_count` |
An integer specify a count number above which where be considerred as 'big' and beta approximation will be used instead for testing differential expression |

### Details

This is the express function for carry out differential expression analysis. Two methods can be choosen from for `paraMethod`

. 'NP' stands for non-parametric method. 'MLE' stands for maximum liklihood estimation method. 'NP' is generally recommended for experiments with replicates smaller than 5.

### Value

A data.frame with following columns:

`id` |
rownames of XBSeqDataSet |

`baseMean` |
The basemean for all genes |

`baseMeanA` |
The basemean for condition 'A' |

`baseMeanB` |
The basemean for condition 'B' |

`foldChange` |
The fold change compare condition 'B' to 'A' |

`log2FoldChange` |
The log2 fold change |

`pval` |
The p value for all genes |

`padj` |
The adjusted p value for all genes |

### Author(s)

Yuanhang Liu

### References

H. I. Chen, Y. Liu, Y. Zou, Z. Lai, D. Sarkar, Y. Huang, et al., "Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads," BMC Genomics, vol. 16 Suppl 7, p. S14, Jun 11 2015.

### See Also

`estimateRealCount`

, `XBSeqDataSet`

, `estimateSCV`

, `XBSeqTest`

### Examples

1 2 3 | ```
conditions <- c(rep('C1', 3), rep('C2', 3))
data(ExampleData)
Stats <- XBSeq(Observed, Background, conditions)
``` |