scranNormalise: scranNormalise
In IMB-Computational-Genomics-Lab/ascend: ascend - Analysis of Single Cell Expression, Normalisation, and Differential expression
Description
Usage
Arguments
Details
Value
Description
Normalise an EMSet with scran's deconvolution
method by Lun et al. 2016.
Usage
1
scranNormalise(object, quickCluster = FALSE, min.mean = 1e-05)
Arguments
object
An EMSet that has not undergone
normalisation.
quickCluster
Use scran's quickCluster method (TRUE) or use randomly-
assigned groups (FALSE, Default).
min.mean
Threshold for average counts. This argument is for the
computeSumFactors function from scran. The value
of 1 is recommended for read count data, while the default value of 1e-5 is
best for UMI data. This argument is only used for newer versions of
scran.
Details
Users may choose to run computeSumFactors using either preset
group sizes (40,60, 80 and 100) or quickCluster. For datasets with over
20,000 cells - it is recommended you use quickCluster.
Value
An EMSet with an expression matrix with counts
normalised by normalize function.
IMB-Computational-Genomics-Lab/ascend documentation built on Aug. 29, 2019, 4:10 a.m.
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Description Usage Arguments Details Value
Description
Normalise an EMSet with scran's deconvolution
method by Lun et al. 2016.
Usage
1 | scranNormalise(object, quickCluster = FALSE, min.mean = 1e-05)
|
Arguments
object |
An |
quickCluster |
Use scran's quickCluster method (TRUE) or use randomly- assigned groups (FALSE, Default). |
min.mean |
Threshold for average counts. This argument is for the
|
Details
Users may choose to run computeSumFactors using either preset group sizes (40,60, 80 and 100) or quickCluster. For datasets with over 20,000 cells - it is recommended you use quickCluster.
Value
An EMSet with an expression matrix with counts
normalised by normalize function.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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