numbat 1.3.3 - 08/15/2023
Fix plotting issue #135
Fix CRAN check compilation issues
numbat 1.3.1 - 04/14/2023
- Fixing bug #68 - this may cause slight changes in the results for runs with
segs_loh/call_segs_lohenabled.
numbat 1.3.0 - 03/31/2023
CRAN release: 2023-04-02
Allows users to supply existing CNV profiles (e.g. from bulk WGS/WES analysis) via
segs_consensus_fixparameterAdding
call_clonal_lohoption to call clonal LOH events withinrun_numbatFixing bug #81
Fixing oversegmentation issue in
find_common_diploidcaused byannot_segs
numbat 1.2.2 - 02/13/2023
CRAN release: 2023-02-14
Introduce
n_cutparameter to specify the number of clones to define from the phylogenyAllows users to redefine subclones from the phylogeny via
nb$cutree
numbat 1.1.0 - 11/28/2022
CRAN release: 2022-11-29
Externalize phylogeny module as separate package (
scistreer)Prepare for new CRAN version
Better CNV state legends for
plot_bulks
numbat 1.0.4 - 11/20/2022
Improving error handling and removing python dependency (
argparse) inpileup_and_phase.RAllows plotting of mutliple annotations in
plot_phylo_heatmap(thanks to @whtns)Adding diagnostic messages
numbat 1.0.3 - 10/09/2022
Fail gracefully when no CNV remains after
retest_bulksPassing
gammaparameter toretest_bulks
numbat 1.0.2 - 09/07/2022
CRAN release: 2022-09-15
Conform to CRAN guidelines
Removed ATC2 examples from package data - users can download from lab server link instead
New option to specify genome version (
genome = 'hg38' or 'hg19'). Support plotting of centromeres and gap regions for hg19.Removed genetic maps from package data and they are no longer provided as input to
run_numbat. Annotation of genetic distance is performed inpileup_and_phase.Rscript instead, using the genetic map included in Eagle2.
numbat 0.1.3 - 07/02/2022
Speed up of NNI using RcppParallel (#34). 10x faster and much more memory efficient (memory requirement is constant with respect to the number of threads).
Speed up of expression single-cell testing using roptim. Approximately 2x speedup.
New LLR metric for CNV filtering that is not inflated (default: 5).
Only keep heterozygous SNPs in alelle dataframe to reduce memory usage
