Add a barplot of the summarizeFasta results

.github/workflows/docs.yaml

@@ -21,6 +21,7 @@ jobs:
           echo 'jinja2==3.0.0' >> requirements.txt
           echo 'mkdocstrings==0.16.2' >> requirements.txt
           echo 'mkdocs-macros-plugin==0.6.0' >> requirements.txt
+          echo 'matplotlib==3.3.1' >> requirements.txt
           echo '.' >> requirements.txt
 
       - name: Deploy docs

.github/workflows/tests.yaml

@@ -26,7 +26,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install biopython pathos pytest psutil six
+          pip install biopython pathos pytest psutil six matplotlib
 
       - name: Run Unit Tests
         run: |

CHANGELOG.md

@@ -24,6 +24,8 @@ This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.htm
 
 - `callAltTranslation` added to call peptides with alternative translation without any genomic or transcriptomic variations.
 
+- Enabled `summarizeFasta` to create bar plot of the summary results.
+
 ### Fixed
 
 - Fixed `fake` that simulated selenocysteine positions could be in introns.

Dockerfile

@@ -4,12 +4,13 @@ COPY . /opt/moPepGen
 
 ARG PYTHON_VER=3.8.11
 ARG BIOPYTHON_VER=1.79
+ARG MATPLOTLIB_VER=3.3.1
 
 RUN conda create -qy -p /usr/local\
     python==${PYTHON_VER}
 
 RUN cd /opt/moPepGen/ && \
-    pip install . biopython==${BIOPYTHON_VER}
+    pip install . biopython==${BIOPYTHON_VER} matplotlib==${MATPLOTLIB_VER}
 
 # Deploy the target tools into a base image
 FROM ubuntu:20.04

moPepGen/aa/PeptidePoolSummarizer.py

@@ -1,7 +1,9 @@
 """ module for peptide pool summarizer """
 from __future__ import annotations
 import itertools
-from typing import Dict, IO, List, Set, FrozenSet, Tuple
+import statistics
+from typing import Dict, IO, List, Set, FrozenSet, Tuple, Optional
+import matplotlib.pyplot as plt
 from moPepGen import gtf, seqvar
 from moPepGen.aa.AminoAcidSeqRecord import AminoAcidSeqRecord
 from moPepGen.aa.VariantPeptideLabel import VariantPeptideInfo, \
@@ -48,6 +50,13 @@
     ]
 }
 
+# BPF default color scheme.
+# Hopefully no one is using more than 11 miscleavages
+COLOR_SCHEME = [
+    "#FFA500", "#458B00", "#68228B", "#FFD700", "#1E90FF", "#CD2626", "#9ACD32"
+    "#FF7F00", "#473C8B", "#43CD80", "#CD3278", "#00C5CD"
+]
+
 class NoncanonicalPeptideSummaryTable():
     """ Summary table for noncaonincal peptides
 
@@ -231,3 +240,65 @@ def write_summary_table(self, handle:IO):
                 key = frozenset(comb)
                 record = self.summary_table.get_stringified_summary_entry(key)
                 handle.write(record + '\n')
+
+    def create_barplot(self, width:float=6, height:float=8, ax:Optional[plt.Axes]=None,
+            scale:str=None) -> plt.Axes:
+        """ Make a barplot of the summarized data. """
+        # misc -> source -> count
+        data:Dict[int,List[int]] = {}
+        keys:List[str] = []
+        sources = [it[0] for it in sorted(self.order.items(), key=lambda x:x[1])]
+        for i in range(len(sources)):
+            for comb in itertools.combinations(sources, i + 1):
+                if self.ignore_missing_source:
+                    # Ignore it if the source isn't present in any GVF given.
+                    if any(not self.summary_table.has_source(k) for k in comb):
+                        continue
+                if self.contains_exclusive_sources(comb):
+                    continue
+                key = frozenset(comb)
+                if key not in self.summary_table.data:
+                    continue
+
+                keys.append('-'.join(key))
+                for x in range(self.summary_table.max_misc + 1):
+                    n = self.summary_table.get_n_x_misc(key, x)
+                    if x not in data:
+                        data[x] = []
+                    data[x].append(n)
+
+        totals = []
+        for x in data.values():
+            if not totals:
+                totals = x
+            else:
+                totals = [i+j for i,j in zip(totals, x)]
+                mean = statistics.mean(totals)
+                median = statistics.median(totals)
+
+        # Unless specified, log scale is used if the summary distribution is skewed.
+        if scale not in ['normal', 'log']:
+            scale = 'normal' if mean / median <= 2.5 else 'log'
+
+        if ax is None:
+            _, ax = plt.subplots(figsize=(width, height))
+
+        if scale == 'log':
+            ax.barh(
+                y=list(reversed(keys)), width=list(reversed(totals))
+            )
+            ax.set_xscale('log')
+        else:
+            offset = None
+            for i,n in enumerate(data.keys()):
+                vals = list(reversed(data[n]))
+                if offset:
+                    vals = [x + y for x,y in zip(vals, offset)]
+                ax.barh(
+                    y=list(reversed(keys)), width=vals, left=offset, label=n,
+                    color=COLOR_SCHEME[i]
+                )
+                offset = vals
+                ax.legend(title='Miscleavages')
+        ax.set_xlabel('Number of Peptides')
+        return ax

moPepGen/cli/summarize_fasta.py

@@ -8,13 +8,15 @@
 from pathlib import Path
 import sys
 from typing import IO
+import matplotlib.pyplot as plt
 from moPepGen.cli import common
 from moPepGen.aa.PeptidePoolSummarizer import PeptidePoolSummarizer
 
 
 GVF_FILE_FORMAT = ['.gvf']
 FASTA_FILE_FORMAT = ['.fasta', '.fa']
 OUTPUT_FILE_FORMATS = ['.txt', 'tsv']
+OUTPUT_IMAGE_FORMATS = ['.pdf', '.jpg', '.jpeg', '.png']
 
 
 # pylint: disable=W0212
@@ -70,11 +72,30 @@ def add_subparser_summarize_fasta(subparser:argparse._SubParsersAction):
         metavar='<file>',
         default=None
     )
+    p.add_argument(
+        '--output-image',
+        type=Path,
+        help=f"File path to the output barplot. Valid formats: {OUTPUT_IMAGE_FORMATS}",
+        metavar='<file>',
+        default=None
+    )
     p.add_argument(
         '--ignore-missing-source',
         action='store_true',
         help='Ignore the sources missing from input GVF.'
     )
+    group_plot_scale = p.add_mutually_exclusive_group()
+    group_plot_scale.add_argument(
+        '--plot-normal-scale',
+        action='store_true',
+        help='Draw the summary bar plot in normal scale.'
+    )
+    group_plot_scale.add_argument(
+        '--plot-log-scale',
+        action='store_true',
+        help='Draw the summary bar plot in log scale.'
+    )
+
     common.add_args_cleavage(p, enzyme_only=True)
     common.add_args_reference(p, genome=False, proteome=True)
     common.add_args_quiet(p)
@@ -102,9 +123,14 @@ def summarize_fasta(args:argparse.Namespace) -> None:
         args.variant_peptides, FASTA_FILE_FORMAT, check_readable=True
     )
 
-    common.validate_file_format(
-        args.output_path, OUTPUT_FILE_FORMATS, check_writable=True
-    )
+    if args.output_path is not None:
+        common.validate_file_format(
+            args.output_path, OUTPUT_FILE_FORMATS, check_writable=True
+        )
+    if args.output_image is not None:
+        common.validate_file_format(
+            args.output_image, OUTPUT_IMAGE_FORMATS, check_writable=True
+        )
 
     common.print_start_message(args)
 
@@ -142,3 +168,14 @@ def summarize_fasta(args:argparse.Namespace) -> None:
 
     with output_context(args.output_path) as handle:
         summarizer.write_summary_table(handle)
+
+    if args.output_image:
+        if args.plot_log_scale:
+            scale = 'log'
+        elif args.plot_normal_scale:
+            scale = 'normal'
+        else:
+            scale = None
+        fig, ax = plt.subplots(figsize=(8, 8))
+        summarizer.create_barplot(ax=ax, scale=scale)
+        fig.savefig(args.output_image, bbox_inches="tight")

setup.cfg

@@ -27,6 +27,7 @@ install_requires =
     psutil
     pathos
     six
+    matplotlib
 
 [options.packages.find]
 where = .

test/integration/test_summarize_fasta.py

@@ -17,6 +17,7 @@ def create_base_args(self) -> argparse.Namespace:
         args.order_source = None
         args.cleavage_rule = 'trypsin'
         args.output_path = self.work_dir/'output.txt'
+        args.output_image = None
         args.ignore_missing_source = False
         args.reference_source = None
         return args