Releases: DominikBuchner/apscale
Releases · DominikBuchner/apscale
1.6.0 released
- updated apscale to work with up-to-date version of pandas
- logs are now read with regex instead of hardcoding to have a more rebust report generation
- bugfixes
1.5.6 released
- fixed future warnings, openpyxl fix still needs to be implemented
1.4.0 released
- update: apscale can now save the OTU table to parquet data format. This is useful for really large datasets that won't fit into excel. parquet can be written and read quickly with python/R/etc. and will be used to handle big data.
1.3.6 released
- many bugfixes
1.3.2 released
- reduced minsize to pool from 5 to 4 in accordance to usearch documentation with regard to "denoising" individual samples. Only sequences with an abundance of at least 3 in one sample of the dataset are used for OTU clustering / denoising.
1.3.1 released
- bugfix in OTU / ESV table generation. Now is faster and consumes less memory
1.3.0 released
- bugfix that stopped apscale from writing the OTU table correctly
1.2.1 released
- minor bugfix on how np.nan's are replaced in the OTU table
1.2.0 released
- OTU and ESV tables are not written line by line and therefore consume constantly low memory. This is important for large datasets.
1.1.1 released
- added an option to dereplicate all samples before adding them to the pooled sequences that are used for clustering. Singletons will still be retained and used for mapping. This greatly reduces the number of spurious OTUs as well as reduces RAM needed for global dereplication. This option can still be omitted by setting the "min size to pool" to 1. Default value is 5.