Description Usage Arguments Value Examples
Creates a SummarizedExperiment object from a data frame containing clonal tracking counts ('your_data') with rows as observations and columns as samples, and the associated metadata ('meta_data') with rows as samples and columns of information describing those samples.
1 2 3 4 5 6 7 8 |
your_data |
A data frame. For clonal tracking data, this will be individual barcodes or lineage tracing elements in rows and samples in columns. |
meta_data |
A data frame containing all meta-data. Must, at the very least, include a column called "SAMPLENAME" that contains all of the colnames within the data frame passed as 'your_data' and only those colnames. |
threshold |
Numeric. The minimum threshold abundance for a barcode to be maintained in the SE. If 'threshold_type' is relative, this parameter should be between 0 and 1. If 'threshold_type' is absolute, this parameter should be greater than 1. |
threshold_type |
Character. One of "relative" or "absolute" relative. If a relative threshold is specified, only those rows which have higher than 'threshold' proportion of reads within at least one sample will be kept as non-zero. If an absolute threshold is specified, only those rows which have an absolute read count higher than 'threshold' in at least one sample will be kept as non-zero. |
log_base |
A numeric indicating which base to use when logging the normalized data |
scale_factor |
A numeric indicating what scaling factor to use in normalization. For the default value of 1 million, barcode proportions on a per sample basis will be multiplied by 1 million before log+1 normalization. |
Returns a SummarizedExperiment holding your clonal tracking data and the associated metadata.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | count_path <- system.file("extdata",
"/WuC_etal_appdata/sample_data_ZJ31.txt",
package = "barcodetrackR"
)
wu_dataframe <- read.delim(count_path, row.names = 1)
metadata_path <- system.file("extdata",
"/WuC_etal_appdata/sample_metadata_ZJ31.txt",
package = "barcodetrackR"
)
wu_metadata <- read.delim(metadata_path)
wu_SE <- create_SE(
your_data = wu_dataframe, meta_data = wu_metadata,
threshold = 0
)
|
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