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

Define per-cell size factors from the geometric mean of counts per cell.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
geometricSizeFactors(x, ...)
## S4 method for signature 'ANY'
geometricSizeFactors(
x,
subset.row = NULL,
pseudo.count = 1,
BPPARAM = SerialParam()
)
## S4 method for signature 'SummarizedExperiment'
geometricSizeFactors(x, ..., assay.type = "counts")
computeGeometricFactors(x, ...)
``` |

`x` |
For For |

`...` |
For the For |

`subset.row` |
A vector specifying whether the size factors should be computed from a subset of rows of |

`pseudo.count` |
Numeric scalar specifying the pseudo-count to add during log-transformation. |

`BPPARAM` |
A BiocParallelParam object indicating how calculations are to be parallelized.
Only relevant when |

`assay.type` |
String or integer scalar indicating the assay of |

The geometric mean provides an alternative measure of the average coverage per cell,
in contrast to the library size factors (i.e., the arithmetic mean) computed by `librarySizeFactors`

.
The main advantage of the geometric mean is that it is more robust to composition biases from a few strongly upregulated genes.

On the other hand, the geometric mean is a poor estimator of the relative bias at low or zero counts. This is because the scaling of the coverage applies to the expectation of the raw counts, so the geometric mean only becomes an accurate estimator if the mean of the logs approaches the log of the mean (usually at high counts). The arbitrary pseudo-count also has a bigger influence at low counts.

As such, the geometric mean is only well-suited for deeply sequenced features, e.g., antibody-derived tags.

For `geometricSizeFactors`

, a numeric vector of size factors is returned for all methods.

For `computeGeometricFactors`

, `x`

is returned containing the size factors in `sizeFactors(x)`

.

Aaron Lun

`normalizeCounts`

and `logNormCounts`

, where these size factors are used by default.

`geometricSizeFactors`

and `medianSizeFactors`

,
for two other simple methods of computing size factors.

1 2 | ```
example_sce <- mockSCE()
summary(geometricSizeFactors(example_sce))
``` |

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