Description Usage Arguments Value Author(s) Examples

View source: R/plotCountDepth.R

Quantile regression is used to estimate the dependence of read counts on sequencing depth for every gene. If multiple conditions are provided, a separate plot is provided for each and the filters are applied within each condition separately. The plot can be used to evaluate the extent of the count-depth relationship in the dataset or can be be used to evaluate data normalized by alternative methods.

1 2 3 4 5 6 7 8 9 10 11 | ```
plotCountDepth(
Data,
NormalizedData = NULL,
Conditions = NULL,
Tau = 0.5,
FilterCellProportion = 0.1,
FilterExpression = 0,
NumExpressionGroups = 10,
NCores = NULL,
ditherCounts = FALSE
)
``` |

`Data` |
can be a matrix of single-cell expression with cells
where rows are genes and columns are samples. Gene names should
not be a column in this matrix, but should be assigned to rownames(Data).
Data can also be an object of class |

`NormalizedData` |
matrix of normalized expression counts. Rows are genesand columns are samples. Only input this if evaluating already normalized data. |

`Conditions` |
vector of condition labels, this should correspond to the columns of the un-normalized expression matrix. If not provided data is assumed to come from same condition/batch. |

`Tau` |
value of quantile for the quantile regression used to estimate gene-specific slopes (default is Tau = .5 (median)). |

`FilterCellProportion` |
the proportion of non-zero expression estimates required to include the genes into the evaluation. Default is .10, and will not go below a proportion which uses less than 10 total cells/samples. |

`FilterExpression` |
exclude genes having median of non-zero expression below this threshold from count-depth plots (default = 0). |

`NumExpressionGroups` |
the number of groups to split the data into, genes are split into equally sized groups based on their non-zero median expression. |

`NCores` |
number of cores to use, default is detectCores() - 1. This will be used to set up a parallel environment using either MulticoreParam (Linux, Mac) or SnowParam (Windows) with NCores using the package BiocParallel. |

`ditherCounts` |
whether to dither/jitter the counts, may be used for data with many ties, default is FALSE. |

returns a data.frame containing each gene's slope (count-depth relationship) and its associated expression group. A plot will be output.

Rhonda Bacher

1 2 3 4 5 | ```
data(ExampleSimSCData)
Conditions = rep(c(1,2), each= 90)
#plotCountDepth(Data = ExampleSimSCData, Conditions = Conditions,
#FilterCellProportion = .1)
``` |

```
```

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