pegasus.log_norm

pegasus.log_norm(data, norm_count=100000.0, backup_matrix='raw.X')[source]

Normalization, and then apply natural logarithm to the data.

Parameters

  • data (pegasusio.MultimodalData) – Use current selected modality in data, which should contain one RNA expression matrix.

  • norm_count (int, optional, default: 1e5.) – Total counts of one cell after normalization.

  • backup_matrix (str, optional, default: raw.X.) – The key name of the backup count matrix, usually the raw counts.

Return type

None

Returns

  • None

  • Update data.X with count matrix after log-normalization. In addition, back up the original count matrix as backup_matrix.

  • In case of rerunning normalization while backup_matrix already exists, use backup_matrix instead of data.X for normalization.

Examples

>>> pg.log_norm(data)