• Updated the logic of using only_oncogenes for filtering.
  • Fixed the data loading for oncogene of mouse.
  • Updated Sequenza workflow.
  • Fixed the re-handling of errored seqz and facets runs.
  • Supported analysis workflow from FACETS and Sequenza.
  • Mouse genome is enabled based on the two implemented workflows above.
  • The first public and stable release.
  • Limited xgboost version lower than 1.6 as it will not keep some key info in .rds file.
  • Enhance the getGeneSummary() and getCytobandSummary() methods to return mutation matrix.
  • This version is not compatible with previous versions, as the analysis and visualization functions are moved to an independent package ‘gcaputils’.
  • Added some utils functions and visualization functions.
  • Updated initial setting and CLI.

This version has been discarded from git history.

  • Supported a NA passing as tightness to remove the use of TCGA blood summary data as a more strict threshold for circular amplicon.
  • Added fCNA$subset() method.
  • Added gcap.plotDistribution() function.
  • Added gcap.plotForest().
  • Added gcap.plotKMcurve().
  • Added gcap.plotProfile().
  • Added method convertGeneID() to fCNA class.
  • Set a default value for pdata option in fCNA$new().
  • Supported gcap as main command, and previous two commands as subcommands if GetoptLong version >=1.1.0. Note: not test yet.
  • Cleaned logic.
  • Added options tightness and gap_cn.
  • Renamed gcap-wes.R script to gcap-bam.R.
  • Handled void result.
  • Updated the background copy number reference and criterion judging a amplicon (#22).
  • Designed and implemented a class fCNA used for storing the workflow key outputs and downstream analysis and visualization.
  • Provided a function convertID() to convert gene IDs.
  • Optimized the output summary.
  • Re-constructed scoring and workflow output.
  • Added use_best_ntreelimit in gcap.runPrediction() to control the ntree setting. When it is FALSE, we use a custom processing to obtain a more conservative tree number.
  • Added deploy() to auto-deploy the CLI to /usr/loca/bin.
  • Added easy-to-use CLI in inst directory.
  • Filled NAs to input when age and gender are not available.
  • Automatically appended logs to specific directory with rappdirs::app_dir("gcap", "ShixiangWang"). Users can obtain log path and cat log info with gcap:::get_log_file() and gcap:::cat_log_file() for debugging. (#14)
  • Supported XGB54 model in workflows. (#13)
  • After exploration, we found our stepwise model outperform MBO tuned model. So the models for predicting circular target have been limited to 3.
  • gcap.ASCNworkflow() now supports input with only total integer copy number, like the result from ABSOLUTE software (also DoAbsolute).
  • Added stepwised model for circle target.
  • Changed the way how to select model and run prediction.
  • custom_model in gcap.runPrediction() has been changed to model. This is inconsistent with version below v0.4.
  • Updated scoring for supporting different thresholds.
  • Wrapped ASCAT workflow in tryCatch() to avoid abnormal failure.
  • Fixed input extra_info sample (order) issues.
  • Fixed the issue about rendering wrong data files when skipping existing ASCAT calling.
  • Updated models for prediction.
  • Removed prob_cutoff setting in workflows. Directly use prob 0.1, 0.5 and 0.9 for cutting low, medium and high quality amplicon.
  • Implemented an alternative workflow from allele specific copy number data to final result files. (#5)
  • Implemented basic workflow from BAM files to result files.
  • Added a NEWS.md file to track changes to the package.