scran_norm
Scaling normalization of single-cell data
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Options for normalize_counts()
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#include <normalize_counts.hpp>
Public Attributes | |
double | pseudo_count = 1 |
bool | preserve_sparsity = false |
bool | log = true |
double | log_base = 2 |
Options for normalize_counts()
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double scran_norm::NormalizeCountsOptions::pseudo_count = 1 |
Pseudo-count to add to each value prior to log-transformation. All values should be positive to ensure that log-transformed values are finite. The default value of 1 preserves sparsity in the log-count matrix. Larger values shrink the differences between cells towards zero, reducing variance at the cost of increasing bias. Ignored if NormalizeCountsOptions::log = false
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bool scran_norm::NormalizeCountsOptions::preserve_sparsity = false |
Whether to preserve sparsity for non-unity pseudo-counts. If true, we multiply the size factors by the pseudo_count
and add 1 before log-transformation. This does not change the differences between entries of the resulting matrix, and adding log(pseudo_count)
will recover the expected log-count values. Ignored if NormalizeCountsOptions::log = false
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bool scran_norm::NormalizeCountsOptions::log = true |
Whether to log-transform the normalized counts in the output matrix.
double scran_norm::NormalizeCountsOptions::log_base = 2 |
Base for the log-transformation. Only used if NormalizeCountsOptions::log = true
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