Feature: tl.peptide_proximity()

.pre-commit-config.yaml

@@ -26,13 +26,22 @@ repos:
     rev: v5.0.0
     hooks:
       # -- Whitespace / EOL hygiene
+      #    tests/data/ is excluded, as it already is for black and
+      #    pyupgrade below. It holds reference output from other tools,
+      #    where trailing whitespace is *data*: an untested proteoform
+      #    group in traces_proteoform-location_rcopf.tsv is a row with
+      #    two empty trailing fields, so stripping them turns a 4-field
+      #    row into a 2-field one. Checksums are recorded in
+      #    tests/data/mouse_tissue/README.md.
       - id: trailing-whitespace
+        exclude: ^tests/data/
         stages: [pre-commit, pre-push]
       - id: end-of-file-fixer
+        exclude: ^tests/data/
         stages: [pre-commit, pre-push]
       - id: mixed-line-ending
         args: ["--fix=lf"]
-        exclude: '\.(bat|cmd|ps1)$'
+        exclude: '(^tests/data/|\.(bat|cmd|ps1)$)'
         stages: [pre-commit, pre-push]
 
       # -- Config-file syntax

HISTORY.md

@@ -9,6 +9,12 @@ and this project adheres to
 
 ### Added
 
+- **Tools** (`pr.tl`): `peptide_proximity()` tests whether the peptides
+  of a proteoform cluster sit closer together in the protein sequence
+  than a random grouping of the same size. A reimplementation of
+  CCprofiler's `evaluateProteoformLocation`, which is the
+  characterisation COPF applies to the proteoform groups it detects.
+
 - **Preprocessing** (`pr.pp`): `summarize_peptides_by_neighbourhood_union()`
   collapses peptides that overlap in the protein sequence, keeping the
   most abundant member of each group. Peptide positions are resolved

docs/sphinx/source/api/tl.rst

@@ -39,4 +39,4 @@ detection of functional proteoform groups from peptide-level quantitative data
    proteopy.tl.peptide_dendograms_by_correlation
    proteopy.tl.peptide_clusters_from_dendograms
    proteopy.tl.proteoform_scores
-
+   proteopy.tl.peptide_proximity

proteopy/tl/__init__.py

@@ -3,10 +3,11 @@
     peptide_dendograms_by_correlation,
     peptide_clusters_from_dendograms,
     proteoform_scores,
-    )
+)
+from .peptide_proximity import peptide_proximity
 from .stat_tests import differential_abundance
 from .clustering import (
     hclustv_tree,
     hclustv_cluster_ann,
     hclustv_profiles,
-    )
+)