Releases: dynverse/dynwrap
dynwrap v1.1.4
dynwrap 1.1.4 (27-06-2019)
- BUG FIX: Fixed #142 where the error message was truncated
dynwrap 1.1.3 (05-06-2019)
-
MINOR CHANGE
add_dimred()
: Add a separate argument for specifying the projected dimred rather than
expecting the projected dimred to be passed as additional columns indimred
. -
BUG FIX: Fix for dynverse/dyno#52, do specify whether or not to use optional priors when passed.
dynwrap 1.1.2 (08-05-2019)
- FEATURE: Add leaves_n as prior information
dynwrap 1.1.1 (08-05-2019)
- BUG FIX: Fixed bug for directed geodesic distances with disconnected gra phs, dynverse/dynplot#37
dynwrap 1.1 (07-05-2019)
-
FEATURE: RNA velocity data can now be included in the wrapper
-
FEATURE: RNA velocity projected expression can now be given to methods
-
FEATURE: Added
orient_topology_to_velocity()
to orient the edges of a trajectory based on the velocity vectors -
FEATURE:
calculate_geodesic_distances()
now has adirected
parameter, with which you can calculate directed geodesic distances. Unreachable cells will receive an infinite distance -
FEATURE: Added
projected_trajectory()
(ported from dynplot).add_dimred()
will now by default also add a projection of the trajectory to the data
dynwrap v1.0.0
dynwrap 1.0.0 (28-03-2019)
-
MAJOR CHANGE: Add support for Singularity 3.0, drop support for previous
releases of Singularity and singularity-hub. -
MAJOR CHANGE: dynwrap now always works with sparse count and expression matrices
-
FEATURE: Add
create_ti_method_definition()
to create a definition from a local script. -
DOCUMENTATION: Major update of all documentation for dynbenchmark publication
-
MINOR CHANGE: Rename
compute_tented_geodesic_distances()
tocalculate_geodesic_distances()
-
MINOR CHANGE: Harmonisation of function arguments to either
dataset
ortrajectory
dynwrap 0.3.1.2 (01-02-2019)
-
BUG FIX:
simplify_replace_edges()
would sometimes swap edges in milestone network around, but forget
invert percentages. -
BUG FIX: Close sinks when interupting the R process
-
MINOR CHANGE: Work with new babelwhale, which includes support for singularity 3.0
dynwrap 0.3.1.1 (17-12-2018)
-
CLEAN UP: Removed helper functions that are not required any more:
get_env_or_null()
,read_rds_or_null()
andprint_processx()
. -
MINOR CHANGE: remove requirement that
milestone_ids
andcell_ids
cannot overlap
dynwrap 0.3.1 (19-11-2018)
- HOTFIX: Use
utils::data()
to get access topriors
.
dynwrap 0.3.0 (19-11-2018)
-
MINOR CHANGE: Added metadata on the different wrapper types implemented in dynwrap.
-
CLEAN UP: Removed
plot_fun
argument fromcreate_ti_method()
. -
MINOR CHANGE: Replaced
mc_cores
with more flexiblemap_fun
. -
MINOR CHANGE: Renamed
create_ti_method()
tocreate_ti_method_r()
,
andcreate_ti_method_with_container()
tocreate_ti_method_container()
. -
CLEAN UP: Drastically reworked
create_ti_method_r()
andcreate_ti_method_container()
,
and the underlying functions for executing a method on a dataset. -
CLEAN UP: Remove
parse_parameter_definition()
and thereby dependency on ParamHelpers.
dynwrap 0.2.0 (29-10-2018)
-
BUG FIX: Fixed incorrect calculation of milestone percentage during trajectory simplification.
Occurs only in a rare edge case, namely when the order of the milestones in the milestone network
is very different from the order of the milestone ids (0475e94). -
BUG FIX: Fixed suggested dependencies not being installed in the dynwrap containers (#100).
-
FEATURE REMOVAL: Removed feather data format because it's not being used and creates dependency issues every now and again.
-
BUG FIX:
devtools:::shim_system.file()
has been moved topkgload:::shim_system.file()
. -
TESTING: Solved issue with the unit tests by not using any helpers.
-
MINOR CHANGE: Have docker images build from dynwrap@devel.
-
BUG FIX: Remove
option(echo = FALSE)
from .Rprofile in recipes because some packages directly rely
on standard output from R, so printing the command wreaks havoc.
dynwrap 0.1.0 (07-03-2018)
- INITIAL RELEASE: dynwrap, functionality for containerised trajectory inference.
- Wrap the input data of a trajectory inference method, such as expression and prior information
- Run a trajectory inference method in R, in a docker container or a singularity container
- Wrap the output of a trajectory inference method, such as the pseudotime, a clustering or a branch network, and convert it into a common trajectory model
- Further postprocess the trajectory model, such as labelling the milestones and rooting the trajectory