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version 0.30.0

This version integrates p-value aggregation as described in Yi et al.. The behavior of gene-level differential expression testing now follows this procedure:

  1. Isoform-level testing.
  2. P-value aggregation at the gene level (using target_mapping) by the lancaster method.

Thank you to Lynn Yi for implementing p-value aggregation. Please see pull request #148 for details.

The API has also slightly changed. Particularly, for sleuth_prep, several options have been moved to optional arguments via .... See pull request #168 for more information or ?sleuth_prep in R.

A fair amount of speed up and bug fixes have also been implemented.

A major thanks to Warren McGee for doing the majority of the heavy lifting on all of the bug fixes.

version 0.29.0

This version has numerous bug fixes and several performance upgrades. Most notably, memory usage has been decreased greatly by no longer storing the bootstraps in memory. Additionally, speed has been improved in numerous areas — particularly sleuth_prep — by changing several of the computations as well as changing the order of the parallelization (special thanks to Warren McGee for his contributions to this).

Below is an incomplete list of new features:

  • The full model no longer has to be specified in sleuth_prep.
  • A new function extract_model allow users to extract the effect sizes for a model in a tidy format similar to broom.
  • An arbitrary transformation can be specified/used in sleuth_prep (see argument transformation_function).

A big thanks to our users for fixing and reporting bugs. A special thanks to Warren McGee for making several of the performance improvements as well as fixing several bugs. Below is a partial list of many of the upgrades and the pull requests by the community.