etl: ETL
In teofiln/gene.editing.dash: VOR Gene Editing Dashboard

Description Usage Arguments Details Value Functions

Run a pipeline to prepare all datasets required by the app

etl(.project)

prep_qc_table(.project_data = NULL, .project = NULL)

prep_qc_barplot_table(.project_data = NULL, .project = NULL)

prep_indel_table(.project_data = NULL, .project = NULL)

prep_alignment_table(.project_data = NULL, .project = NULL)

prep_allele_table(.project_data = NULL, .project = NULL)

`.project`	character, the project id. Only data belonging to this project will be prepared for loading into the app
`.project_data`	list, a list of datasets

In 'production' mode, the app will load required datasets after the user chooses a project id string. For testing individual functions, we can supply a data object directly to the function.

A list of three lists:

$meta, a list of one data frame with the metadata corresponding to .project
$data, a list of six data frames with the raw data corresponding to .project
$app, a list of four tables merging or transforming objects from $data to be used by app modules

prep_qc_table: Merge CRISPRSummary and QCTable to calculate the percent of usable reads to display in the read qc module
prep_qc_barplot_table: Merge the SampleMeta and EditingFreq datasets to generate a barplot of the percent modified/unmodified reads per sample to display in the read qc barplot module
prep_indel_table: Merge the SampleMeta and IndelFreq datasets to generate a scatter plot of the indel species distribution, later displayed in the the indel distributon module
prep_alignment_table: Transform the AlleleAlignFreq table for loading into the app, to display in the sequence alignment module
prep_allele_table: Transform the AlleleAlignFreq table for loading into the app, to display in the allele frequency module