CELLECT-GENES

CELLECT-GENES is a workflow to identify genes 'driving' the prioritization of cell types. These genes are found by intersecting the top specifically expressed genes with genes enriched for genetic signal.
See CELLECT-GENES tutorial for details

CELLECT-MAGMA

Added

• CELLECT-MAGMA implemented (analysis types supported: prioritization, conditional).
• Extra output directory layer. The results are output into 2 separate subdirectories of the base output directory: CELLECT-LDSC and CELLECT-MAGMA respectively.

Changed

• Minimized the overlap of functions between CELLECT-LDSC and CELLECT-MAGMA via includes.
• Config file. The file was divided into sections of common and LDSC-/MAGMA-specific parameters.
• WiKi (respective sections for CELLECT-LDSC)
• README Documentation

Improved CELLECT-LDSC handling of continuous gene annotations

From CHANGELOG.md

Added

• Improved README.md information

Changed

• Improved CELLECT-LDSC handling of continuous gene annotations. Importantly, this changes the prioritization results slightly.
  CELLECT v. 1.1.0 and 1.0.0 produce prioritization results with Pearson's correlation ~0.95.

Removed

• Redundant "make multigeneset" functionality

Fixed

• Some legacy references to incorrect paths
• Reduced conda envs dependencies

Technical details

See commit for overview of important changes: c7513a1
See also #8 for a description of the problem.

• Replaced use of BEDtools for merging overlapping genes into a single track with BEDOPs which finds all unique overlapping regions and is more appropriate for continuous data
• General restructuring of rules and scripts to account for above
• Added BEDOPs to env
• Some additional tidying and minor bugfixes

CELLECT S-LDSC prioritization

First stable release for CELLECT S-LDSC prioritization. No support for S-LDSC h2 or conditional analysis.

CELLECT S-LDSC

Major updates:

• Support for LDSC conditional and h2 analysis types
• Added result parser

This version of the software was used for BMI cell-type heritability mapping (Timshel, submitted https://github.com/perslab/timshel-bmicelltypes2019)