# SingleCellAlleleExperiment 1.0.2

Fixed error in tests

# SingleCellAlleleExperiment 1.0.1

Updated allele names in the vignette after data package "scaeData" was updated

# SingleCellAlleleExperiment 0.99.5

Changes regarding the second round of comments during the Bioconductor submission
review:

- Minor changes to SCAE-show method
- Extended and moved installation-checks for packages used in optional
functionalities to the SCAE-constructor
- Extended checks for the rowData setter

- Extended unit tests to increase coverage


# SingleCellAlleleExperiment 0.99.4

Changes regarding the first round of comments during the Bioconductor submission
review:

 Removed multiple dependencies, now listed as suggested
 - computation of the logcounts assay now optional
 - computation of a knee plot and according inflection/knee points now optional
 - computation of new gene-symbols now optional
 
 - minor changes in tests (needs to be extended to test for new optional code);
 also extension of the tests to check new code
 
 - major changes in package structure and organisation
 
 - reworked vignette to include optional features
 
# SingleCellAlleleExperiment 0.99.3

- retriggering bioc build during package submission.

# SingleCellAlleleExperiment 0.99.2

- minor changes in the vignette to reduce build-time. Content is the same.

# SingleCellAlleleExperiment 0.99.1

- minor changes made regarding the Bioconductor submission review of `scaeData` which also affected this package.


# SingleCellAlleleExperiment 0.99.0 

* The package is defining a S4 class that is extending the SingleCellExperiment class.
  The multi-layer data structure integrates data for immune genes at allele and 
  functional level.
  
* **Workflow**: To be able to generate a `SingleCellAlleleExperiment` object the data has
  to be generated by the connected workflow `single-cell ImmunoGenomic Diversity (scIGD)`
  which performs allele typing and quantification of genes and typed alleles.
  Use the `read_allele_counts()` function to read in the data and generate an 
  SCAE object. This function also offers parameters to perform filtering on the data,
  as well as visualize the filtering step in a so called `knee plot`.
  
