Fix clean code (#64)

.github/workflows/ci.yml

@@ -6,6 +6,9 @@ on:
   pull_request:
     branches: main
     paths: ["src/**", "tests/**", ".github/workflows/**"]
+  schedule:
+    # Scheduled Daily CI
+    - cron: "0 0 * * *"
 
 jobs:
   CI_black-flake8-pytest:

README.md

@@ -1,4 +1,4 @@
-# FastDTLmapper: Fast genome-wide DTL event mapper  
+# FastDTLmapper: Fast genome-wide DTL event mapper
 
 ![Python3](https://img.shields.io/badge/Language-Python_3.7_|_3.8_|_3.9-steelblue)
 ![OS](https://img.shields.io/badge/OS-Linux-steelblue)
@@ -24,7 +24,7 @@ driving adaptive evolution, but it remains largely unexplored.
 Therefore, to investigate the relationship between gene gain/loss and adaptive evolution
 in the evolutionary process of organisms, I developed a software pipeline **FastDTLmapper**
 which automatically estimates and maps genome-wide gene gain/loss.  
-FastDTLmapper takes two inputs, 1. *Species tree (Newick format)* 2. *Genomic Protein CDSs (Fasta|Genbank format)*,
+FastDTLmapper takes two inputs, 1. *Species tree (Newick format)* & 2. *Genomic Protein CDSs (Fasta|Genbank format)*,
 and performs genome-wide mapping of DTL(Duplication-Transfer-Loss) events by
 DTL reconciliation of species tree and gene trees.
 Additionally, FastDTLmapper can perform
@@ -162,25 +162,25 @@ This is brief description of analysis pipeline. See [wiki](https://github.com/mo
     --dup_cost            Duplication event cost (Default: 2)
     --los_cost            Loss event cost (Default: 1)
     --trn_cost            Transfer event cost (Default: 3)
-    --inflation           OrthoFinder MCL inflation parameter (Default: 3.0)
+    --inflation           OrthoFinder MCL inflation parameter (Default: 1.5)
     --timetree            Use species tree as timetree in AnGST (Default: off)
     --rseed               Number of random seed (Default: 0)
 
-#### Timetree Option
+- **Timetree Option**
 
-If user set this option, input species tree must be ultrametric tree.  
---timetree enable AnGST timetree option below (See [AnGST manual](<https://github.com/almlab/angst/blob/master/doc/manual.pdf>) for details).  
-> If the branch lengths on the provided species tree represent times,
-> AnGST can restrict the set of possible inferred gene transfers to
-> only those between contemporaneous lineages  
+  If user set this option, input species tree must be ultrametric tree.  
+  --timetree enable AnGST timetree option below (See [AnGST manual](<https://github.com/almlab/angst/blob/master/doc/manual.pdf>) for details).  
+  > If the branch lengths on the provided species tree represent times,
+  > AnGST can restrict the set of possible inferred gene transfers to
+  > only those between contemporaneous lineages  
 
-#### Input Limitation
+- **Input Limitation**
 
-fasta or genbank files (--indir option)  
->:warning: Following characters cannot be included in file name '_', '-', '|', '.'  
+  fasta or genbank files (--indir option)  
+  >:warning: Following characters cannot be included in file name '_', '-', '|', '.'  
 
-species tree file (--tree option)  
->:warning: Species name in species tree must match fasta or genbank file name  
+  species tree file (--tree option)  
+  >:warning: Species name in species tree must match fasta or genbank file name  
 
 ### Example Command
 
@@ -190,23 +190,23 @@ Download example dataset:
 
 This dataset is identical to [example](https://github.com/moshi4/FastDTLmapper/tree/main/example) in this repository.
 
-#### 1. Minimum test dataset
+- **Minimum test dataset**
 
-7 species, 100 CDS limited fasta dataset
+  7 species, 100 CDS limited fasta dataset
 
-    FastDTLmapper -i example/minimum_dataset/fasta/ -t example/minimum_dataset/species_tree.nwk -o output_minimum
+      FastDTLmapper -i example/minimum_dataset/fasta/ -t example/minimum_dataset/species_tree.nwk -o output_minimum
 
-#### 2. Mycoplasma dataset (Input Format = Fasta)
+- **Mycoplasma dataset (Input Format = Fasta)**
 
-7 Mycoplasma species, 500 ~ 1000 CDS fasta dataset
+  7 Mycoplasma species, 500 ~ 1000 CDS fasta dataset
 
-    FastDTLmapper -i example/mycoplasma_dataset/fasta/ -t example/mycoplasma_dataset/species_tree.nwk -o output_mycoplasma_fasta
+      FastDTLmapper -i example/mycoplasma_dataset/fasta/ -t example/mycoplasma_dataset/species_tree.nwk -o output_mycoplasma_fasta
 
-#### 3. Mycoplasma dataset (Input Format = Genbank)
+- **Mycoplasma dataset (Input Format = Genbank)**
 
-7 Mycoplasma species, 500 ~ 1000 CDS genbank dataset
+  7 Mycoplasma species, 500 ~ 1000 CDS genbank dataset
 
-    FastDTLmapper -i example/mycoplasma_dataset/genbank/ -t example/mycoplasma_dataset/species_tree.nwk -o output_mycoplasma_genbank
+      FastDTLmapper -i example/mycoplasma_dataset/genbank/ -t example/mycoplasma_dataset/species_tree.nwk -o output_mycoplasma_genbank
 
 ## Output Contents
 
@@ -256,6 +256,8 @@ This dataset is identical to [example](https://github.com/moshi4/FastDTLmapper/t
         ├── parallel_cmds/ -- Parallel run command log results
         └── run_config.log -- Program run config log file
 
+See [wiki](https://github.com/moshi4/FastDTLmapper/wiki/1.2.-Output-Contents-(FastDTLmapper)) for output files details.
+
 ## Further Analysis
 
 ### Plot Gain/Loss Map Figure

src/fastdtlmapper/args.py

@@ -6,6 +6,7 @@
 import sys
 import time
 from dataclasses import dataclass
+from enum import IntEnum, auto
 from pathlib import Path
 from typing import List, Optional, Union
 
@@ -66,6 +67,18 @@ def unixtime_to_datestr(unixtime: float) -> str:
         return log_text
 
 
+class RestartFrom(IntEnum):
+    """RestartFrom Enum Class"""
+
+    ORTHO_FINDER = auto()
+    MAFFT = auto()
+    TRIMAL = auto()
+    IQTREE = auto()
+    TREERECS = auto()
+    ANGST = auto()
+    AGG_MAP = auto()
+
+
 def get_args(argv: Optional[List[str]] = None) -> Args:
     """Get arguments
 
@@ -135,7 +148,7 @@ def get_args(argv: Optional[List[str]] = None) -> Args:
         default=default_trn_cost,
         metavar="",
     )
-    default_inflation = 3.0
+    default_inflation = 1.5
     parser.add_argument(
         "--inflation",
         type=float,
@@ -145,7 +158,7 @@ def get_args(argv: Optional[List[str]] = None) -> Args:
     )
     parser.add_argument(
         "--timetree",
-        help="Use species tree as timetree",
+        help="Use species tree as timetree in AnGST (Default: off)",
         action="store_true",
     )
     default_rseed = 0
@@ -163,8 +176,8 @@ def get_args(argv: Optional[List[str]] = None) -> Args:
         "--restart_from",
         type=int,
         help=argparse.SUPPRESS,
-        default=1,
-        choices=[1, 2, 3, 4, 5, 6, 7],
+        default=RestartFrom.ORTHO_FINDER,
+        choices=[rf.value for rf in RestartFrom],
     )
 
     args = parser.parse_args(argv)

src/fastdtlmapper/goea/goea.py

@@ -58,41 +58,44 @@ def run(self, output_prefix: Path) -> List[Path]:
     def plot(
         self,
         goea_result_file: Path,
-        output_prefix: Path,
+        plot_outfile: Path,
+        over_or_under: str,
+        title: str = "",
     ) -> None:
         """Plot GOEA significant GOterms
 
         Args:
             goea_result_file (Path): GOEA result file path
-            output_prefix (Path): Output files prefix path
+            plot_outfile (Path): Output file path
+            over_or_under (str): "over" or "under"
+            title (str): Plot title
         """
-        for goea_type in ("over", "under"):
-            # Extract goterm & pvalue
-            goterm2pvalue = self._extract_goterm2pvalue(goea_result_file, goea_type)
-            if len(goterm2pvalue) == 0:
-                continue
+        if over_or_under not in ("over", "under"):
+            raise ValueError("goea_type must be 'over' or 'under'")
 
-            # Plot color setting
-            goterm2hexcolor = {}
-            if self.plot_color:
-                # Set specified plot color
-                for goterm in goterm2pvalue.keys():
-                    goterm2hexcolor[goterm] = self.plot_color
-            else:
-                # Get hexcolor from pvalue for color plot
-                pvalue_abs_log10_list = [
-                    abs(math.log10(v)) for v in goterm2pvalue.values()
-                ]
-                pvalue_hexcolor_list = self._convert_hexcolor_gradient(
-                    pvalue_abs_log10_list
-                )
-                # Set yellow to red gradient plot color
-                for goterm, hexcolor in zip(goterm2pvalue.keys(), pvalue_hexcolor_list):
-                    goterm2hexcolor[goterm] = hexcolor
-
-            # Plot GOterm with gradient color
-            plot_outfile = Path(f"{output_prefix}_{goea_type}.{self.plot_format}")
-            self._color_plot(plot_outfile, goterm2hexcolor, goterm2pvalue)
+        # Extract goterm & pvalue
+        goterm2pvalue = self._extract_goterm2pvalue(goea_result_file, over_or_under)
+        if len(goterm2pvalue) == 0:
+            return
+
+        # Plot color setting
+        goterm2hexcolor = {}
+        if self.plot_color:
+            # Set specified plot color
+            for goterm in goterm2pvalue.keys():
+                goterm2hexcolor[goterm] = self.plot_color
+        else:
+            # Get hexcolor from pvalue for color plot
+            pvalue_abs_log10_list = [abs(math.log10(v)) for v in goterm2pvalue.values()]
+            pvalue_hexcolor_list = self._convert_hexcolor_gradient(
+                pvalue_abs_log10_list
+            )
+            # Set yellow to red gradient plot color
+            for goterm, hexcolor in zip(goterm2pvalue.keys(), pvalue_hexcolor_list):
+                goterm2hexcolor[goterm] = hexcolor
+
+        # Plot GOterm with gradient color
+        self._color_plot(plot_outfile, goterm2hexcolor, goterm2pvalue, title)
 
     def _extract_goterm2pvalue(
         self,
@@ -181,13 +184,15 @@ def _color_plot(
         plot_outfile: Union[str, Path],
         goid2color: Dict[str, str],
         goid2pvalue: Dict[str, float] = {},
+        title: str = "",
     ) -> None:
         """Plot GO DAG using self-defined GO color
 
         Args:
             plot_outfile (str): Output plot file path
             goid2color (Dict[str, str]): go id and hexcolor dict
             goid2pvalue (Dict[str, float], optional): go id and pvalue dict
+            title (str): Plot title
         """
         # Get plot target GO DAG
         obodag = GODag(self.obo_file)
@@ -214,16 +219,6 @@ def _color_plot(
         godag_plg_vars = GODagPltVars()
         godag_plg_vars.fmthdr = "{GO}"
 
-        # Plot title
-        title = Path(plot_outfile).with_suffix("").name.replace("_", " ")
-        title += " representation\n"
-        title += f"Top{self.plot_max_num} GOterm "
-        if self.use_adjusted_pvalue:
-            title += f"(BH adjusted P-value < {self.pvalue_thr})"
-        else:
-            title += f"(P-value < {self.pvalue_thr})"
-        title = f"\n{title}\n"
-
         # Create plot obj & add plot color
         godagplot = GODagSmallPlot(
             godagsmall, abodag=obodag, GODagPltVars=godag_plg_vars, title=title

src/fastdtlmapper/out_path.py

@@ -52,7 +52,7 @@ def __post_init__(self):
         self.result_summary_dir = self.goea_dir / "result_summary"
         self.result_summary_plot_dir = self.result_summary_dir / "significant_go_plot"
 
-        self.obo_file = self.goea_dir / "go-basic.obo"
+        self.obo_file = self.go_enrichment_dir / "go-basic.obo"
         self.og2go_association_file = self.go_enrichment_dir / "og2go_association.txt"
         self.significant_go_list_file = (
             self.result_summary_dir / "significant_go_list.tsv"

src/fastdtlmapper/scripts/FastDTLgoea.py

@@ -224,7 +224,21 @@ def run_goatools_goea(
         goea_result_file_list = goea.run(output_prefix)
         # Plot GOEA significant GOterms
         for goea_result_file in goea_result_file_list:
-            goea.plot(goea_result_file, goea_result_file.with_suffix(""))
+            for over_or_under in ("over", "under"):
+                go_category = str(goea_result_file.with_suffix("")).split("_")[-1]
+                # Define title
+                title = f"{node_id} {gain_or_loss} {over_or_under} representation\n"
+                title += f"Top{plot_max_num} {go_category} GOterm "
+                if use_adjusted_pvalue:
+                    title += f"(BH adjusted P-value < {pvalue_thr})"
+                else:
+                    title += f"(P-value < {pvalue_thr})"
+                title = f"\n{title}\n"
+
+                plot_outfile = Path(
+                    f"{output_prefix}_{over_or_under}_{go_category}.{plot_format}"
+                )
+                goea.plot(goea_result_file, plot_outfile, over_or_under, title)
 
 
 if __name__ == "__main__":