0.4

What's Changed

• Glm pca devel by @vivekbhr in #21
• Documentation updates by @vivekbhr in #23
• added logPCA (scanpy) option for clustering by @vivekbhr in #24

Full Changelog: 0.3.1...0.4

0.3.1

bugfix + doc changes

• Consistent file headers for scFilterStats and scCountQC, to allow multiQC parsing
• Argparse and docs improved
• Deduplication: avoid overcounting due to chimeric fragments or mismatched reference pos

glmPCA release

• New in scClusterCells:
  • glmPCA with several distributions.
  • LSA/LDA moved to the topicmodels class
• Bugfix:
  • scFilterBarcodes: outfile
  • scBAMops: renamed tool (WIP for v0.4: adding cell groups by barcode)
• Code re-factored to new python style (pep621)

v0.2

More features:

• scCombineCounts: to concatenate counts from multiple runs of scCountReads
• scCountReads: Ability to group by SM tag, ability to output region name in case of BED/GTF input
• other minor updates and bugfixes

v0.1

Following tools are supported:

scFilterBarcodes      Identify and filter cell barcodes from BAM file (for droplet-based single-cell seq)
scFilterStats             Produce per-cell statistics after filtering reads by user-defined criteria.
scCountReads         Counts reads for each barcode on genomic bins or user-defined features.
scCountQC              Perform quality control and filter the output of scCountReads.
scCombineCounts    Concatenate/merge the counts from different samples/batches or modalities
scClusterCells          Perform dimensionality reduction and clustering on the output of scCountReads.
scBulkCoverage       Get pseudo-bulk coverage per group using a user-supplied cell->group mapping (output of scClusterCells).