buildExpressionSummary: Calculates average expression levels of the results of a...
In CharlesJB/ENCODExplorer: A compilation of ENCODE metadata

Description Usage Arguments Value Examples

This function takes the result of a previous call to queryEncode, splits the contained expression files by conditions (as specified by the split_by argument), then calculates average expression levels for each condition.

buildExpressionSummary(
  query_results,
  split_by,
  metric = NULL,
  simplify = FALSE,
  aggregate_function = mean,
  temp_dir = ".",
  force = FALSE
)

`query_results`	A data.table returned by `queryEncode` or `queryEncodeGeneric`.
`split_by`	A vector of column names from query_results that will be used to split the average expression levels. If `NULL`, all elements of query_results are used in the same average expression calculation.
`metric`	A regular expression, indicating which column from the ENCODE data must be extracted. If NULL, ENCODExplorer data automatically detects and selects one of the TPM, FPKM or featurecount columns.
`simplify`	If TRUE, non-discriminatory columns are removed from the metadata, and if only one sample group is found, it is renamed "All".
`aggregate_function`	A function which takes a vector as input and returns a single value summarizing the whole. Used to summarize expression metrics.
`temp_dir`	The path to a directory where peak files will be downloaded.
`force`	A logical indicating whether already present files be redownloaded.

An object of class ENCODEExpressionSummary.

query_results = queryEncodeGeneric(biosample_name="neural tube", 
                                   output_type="gene quantifications",
                                   file_type="tsv",
                                   assay="polyA plus RNA-seq",
                                   assembly="^mm10$",
                                   dataset_biosample_summary="(15.5|13.5)",
                                   fixed=FALSE)
                                   
buildExpressionSummary(query_results, split_by="dataset_biosample_summary")