capcruncher 0.2.3

An end-to-end solution for processing Capture-C, Tri-C and Tiled-C data

CapCruncher

Analysis software for Capture-C, Tri-C and Tiled-C data.

CapCruncher is a tool designed to automate the processing of Capture-C, Tri-C and Tiled-C data from FASTQ files, the package is written in python and consists of an end-to-end data processing pipline together with a supporting command line interface to enable finer grained control. The pipeline provided is fast, robust and scales from a laptop to a computational cluster.

For further information see the documentation

Changelog

[0.2.3] - 2022-08-19

Bug Fixes

• Fixes Tiled-C filtering error due to typo in index specification for remove_dual_capture_fragments
• Fixed bug when annotating Tiled-C data (#166) with the sorted option that caused no data to be annotated as as a viewpoint or exclusion.
• Fixed a bug with Tiled-C slice filtering (#166) that caused slices to be erronously filtered.
• Fixed a bug with counting reporters in batches (this occurs when counting >1x106 slices per viewpoint) (#166)
• Fixed a bug when merging and storing Tri-C or Tiled-C data (#166) using "capcruncher reporters store merge" or "capcruncher reporters store bins". This functionally has been re-written and now appears to work correctly.
• Fixed a bug with plotting matrices using capcrunchers plotting capabilities (#166).
• Fixes bug where all slices are removed from parquet files (reporter) outputs due to an upgraded dask version (the pyarrow-dataset engine has been removed). This corrects the all dataframes are empty error occurring while generating reporter statistics.

Features

• Added option to normalised CCMatrix data using ice followed by a scaling factor.
• Reporter merging (paraquet) has been re-written to use pyarrow directly and is now faster and better able to split datasets into smaller files for more efficient parallel querying.

Miscellaneous Tasks

• Updated version to 0.2.3 (#165)
• Pin conda dependency versions to speed up environment solver (#167)