Description Usage Arguments Details Value Note Author(s) References See Also Examples

This function implements CQN (conditional quantile normalization) for RNA-Seq data.

1 2 3 4 |

`counts` |
An object that can be coerced to a |

`x` |
This is a covariate whose systematic influence on the counts will be removed. Typically the GC content. Has to have the same length as the number of rows of counts. |

`lengths` |
The lengths (in bp) of the regions in counts. Has to have the same length as the number of rows of counts. |

`sizeFactors` |
An optional vector of sizeFactors, ie. the sequencing effort of the
various samples. If |

`subindex` |
An optional vector of indices into the rows of |

`tau` |
This argument is passed to |

`sqn` |
This argument indicates whether the residuals from the systematic fit are (subset) quantile normalized. The default should only be changed by expert users. |

`lengthMethod` |
Should length enter the model as a smooth function or not. |

`verbose` |
Is the function verbose? |

`...` |
Not used. |

These functions implement the CQN (conditional quantile normalization)
for RNA-Seq data. The functions remove a single systematic effect,
contained in the argument `x`

, which will typicall be GC
content. The effect of `lengths`

will either be modelled as a
smooth function (which we recommend), if you are using
`lengthMethod = "smooth"`

or
as an offset (equivalent to modelling using RPKMs), if you are using
`lengthMethod = "fixed"`

. Length can be complete removed from
the model by having `lengthMethod = "fixed"`

and setting all
lengths to 1000.

Final corrected values are equal to `value$y + value$offset`

.

A `list`

with the following components

`counts` |
The value of argument |

`x` |
The value of argument |

`lengths` |
The value of argument |

`sizeFactors` |
The value of argument |

`subindex` |
The value of argument |

`y` |
The dependent value used in the systematic effect fit. Equal to log2 tranformed reads per millions. |

`offset` |
The estimated offset. |

`offset0` |
A single number used internally for identifiability. |

`glm.offset` |
An offset useful for supplying to a GLM type model function. It is on the natural log scale and includes correcting for sizeFactors. |

`func1` |
The estimated effect of function 1 (argument |

`grid1` |
The grid points on which function 1 (argument |

`knots1` |
The knots used for function 1 (argument |

`func2` |
The estimated effect of function 2 (lengths). This is a matrix of function values on a grid. Columns are samples and rows are grid points. |

`grid2` |
The grid points on which function 2 (lengths) was evaluated. |

`knots2` |
The knots used for function 2 (lengths). |

`call` |
The call. |

Internally, the function uses a custom implementation of subset
quantile normalization, contained in the (not exported) `SQN2`

function.

Kasper Daniel Hansen, Zhijin Wu

KD Hansen, RA Irizarry, and Z Wu, Removing technical variability in RNA-seq data using conditional quantile normalization. Biostatistics 2012 vol. 13(2) pp. 204-216.

The package vignette.

1 2 3 4 5 6 | ```
data(montgomery.subset)
data(sizeFactors.subset)
data(uCovar)
cqn.subset <- cqn(montgomery.subset, lengths = uCovar$length,
x = uCovar$gccontent, sizeFactors = sizeFactors.subset,
verbose = TRUE)
``` |

```
Loading required package: mclust
Package 'mclust' version 5.4.2
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: nor1mix
Loading required package: preprocessCore
Loading required package: splines
Loading required package: quantreg
Loading required package: SparseM
Attaching package: 'SparseM'
The following object is masked from 'package:base':
backsolve
RQ fit ..........
SQN Using 'sigma' instead 'sig2' (= sigma^2) is preferred now
.
```

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