2026-08-02

.envrc

@@ -4,5 +4,3 @@ export SCRIPTS="$PROJECTHOME/99.scripts"
 export PUEUE_CONFIG_PATH="$PROJECTHOME/.pueue.yml"
 watch_file pixi.lock
 eval "$(pixi shell-hook)"
-PATH_add $SCRIPTS/bucky/bin
-PATH_add $SCRIPTS/bpp/bin

.gitignore

@@ -12,7 +12,11 @@
 06.phylogeny_reconstruction/*
 06.phylogenetic_analysis/*
 06.gene_trees/*
+07.species_tree/*
+07.coalescence_network/*
 10.plastid/*
+11.reference_v2/*
+12.orthofinder/*
 98.results/*
 99.scripts/bucky/
 99.scripts/phyparts/

99.scripts/miscs/make_bpp_seq.py

@@ -0,0 +1,84 @@
+#!/usr/bin/env python
+"""
+Prepare input sequence file from fasta file in a directory for BPP.
+"""
+
+import argparse
+import sys
+from pathlib import Path
+from Bio import SeqIO
+
+
+def get_fasta_files(input_dir: Path, ext=".fasta") -> list[Path]:
+    """
+    Get a list of fasta files in the specified directory with the given extension.
+    Args:
+        input_dir (Path): Path to the directory containing fasta files.
+        ext (str): Extension of the fasta files.
+    Returns:
+        list[Path]: List of Paths to the fasta files.
+    """
+    files = list(input_dir.glob(f"*{ext}"))
+    if not files:
+        print(f"No fasta files with extension '{ext}' found in directory '{input_dir}'")
+        sys.exit(1)
+    return files
+
+
+def transform_fasta_to_bpp(fasta_file: Path):
+    """
+    Transform a fasta file into BPP sequence format.
+    Args:
+        fasta_file (Path): Path to the input fasta file.
+    Returns:
+        list[str]: Lines formatted for BPP input.
+    """
+    num_ind = 0
+    output_lines = []
+    seq_len = []
+    for record in SeqIO.parse(fasta_file, "fasta"):
+        ind_id = record.id
+        num_ind += 1
+        output_lines.append(f"^{ind_id}    {str(record.seq)}\n")
+        seq_len.append(len(record.seq))
+    if len(set(seq_len)) != 1:
+        print(f"Error: Sequences in file '{fasta_file}' have different lengths.")
+        sys.exit(1)
+    header = f"{num_ind} {seq_len[0]}\n"
+    return [header, "\n", *output_lines, "\n"]
+
+
+def make_bpp_seq(input_dir: Path, output_file: Path, ext=".fasta"):
+    """
+    Create a BPP formatted sequence file from fasta files in a directory.
+    Args:
+        input_dir (Path): Path to the directory containing fasta files.
+        output_file (Path): Path to the output BPP formatted file.
+        ext (str): Extension of the fasta files.
+    """
+    fasta_files = get_fasta_files(input_dir, ext)
+    with open(output_file, "w") as out_f:
+        for fasta_file in fasta_files:
+            bpp_lines = transform_fasta_to_bpp(fasta_file)
+            out_f.writelines(bpp_lines)
+    print(f"BPP formatted sequence file written to '{output_file}'")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Create a BPP formatted sequence file from fasta files in a directory."
+    )
+    parser.add_argument(
+        "input_dir", type=Path, help="Directory containing fasta files."
+    )
+    parser.add_argument(
+        "output_file", type=Path, help="Output BPP formatted sequence file."
+    )
+    parser.add_argument(
+        "--ext",
+        type=str,
+        default=".fasta",
+        help="Extension of the fasta files (default: .fasta).",
+    )
+    args = parser.parse_args()
+    make_bpp_seq(args.input_dir, args.output_file, args.ext)

99.scripts/workflow/coalescence_network/bpp/README.md

@@ -0,0 +1,89 @@
+# BPP Coalescence Network Analysis Scripts
+
+This directory contains scripts for running BPP (Bayesian Phylogenetics & Phylogeography) analysis using the A00 method for coalescence network inference.
+
+## Files
+
+1. `run_bpp_a00.ctl` - Control file for BPP A00 analysis
+2. `run_bpp.sh` - Shell script to execute the BPP analysis
+3. `generate_and_run_bpp.py` - Python script to generate control file and run BPP analysis
+4. `README.md` - This file
+
+## Prerequisites
+
+1. BPP software must be installed and available in your PATH
+2. Input sequence data in PHYLIP format
+3. Imap file mapping sequences to species
+4. Known species tree topology
+
+## Usage
+
+### Method 1: Manual Control File Editing
+1. Update the control file (`run_bpp_a00.ctl`) with your specific:
+   - Sequence file path (`seqfile`)
+   - Imap file path (`Imapfile`)
+   - Species names, counts, and tree topology in `species&tree` block
+   - Number of loci (`nloci`)
+   - Other parameters as needed
+
+2. Prepare your input files:
+   - Sequence file in PHYLIP format with multiple loci
+   - Imap file mapping individual sequences to species
+   - Ensure your species tree topology is correct
+
+3. Run the analysis:
+   ```bash
+   ./run_bpp.sh
+   ```
+
+### Method 2: Automated Python Script (Recommended)
+Use the Python script to automatically generate the control file and run the analysis:
+
+```bash
+python generate_and_run_bpp.py \
+  --seqfile sequences.txt \
+  --imapfile species_map.txt \
+  --species sp1 sp2 sp3 sp4 sp5 \
+  --nloci 100 \
+  --output my_analysis_result \
+  --threads 8 \
+  --burnin 20000 \
+  --nsample 100000 \
+  --sampfreq 5
+```
+
+## BPP A00 Analysis Mode
+
+The A00 analysis mode is appropriate for your use case because:
+- You have one sample per species
+- You have a known species tree (systematic network)
+- You want to estimate population size (θ) and divergence time (τ) parameters
+
+In this mode:
+- `speciesdelimitation = 0` - Species delimitation is fixed
+- `speciestree = 0` - Species tree is fixed
+- Parameters θ and τ are estimated on the fixed tree
+
+## Key Parameters in Control File
+
+- `thetaprior`: Inverse gamma prior for population size parameters (θ)
+- `tauprior`: Inverse gamma prior for root divergence time, Dirichlet for others
+- `burnin`: Number of burn-in iterations for MCMC
+- `nsample`: Number of samples to collect
+- `sampfreq`: Sampling frequency
+- `threads`: Number of CPU threads to use
+
+## Output Files
+
+After successful execution, you will get:
+- Main output file (default: `bpp_a00_results.txt`)
+- MCMC samples file (default: `bpp_a00_results.mcmc.txt`)
+- Seed information file (default: `bpp_a00_results.SeedUsed`)
+
+## Customization
+
+Depending on your data characteristics, you may want to adjust:
+- Prior parameters for θ and τ
+- MCMC settings (burnin, nsample, sampfreq)
+- Threading options
+- Output options in the `print` line

99.scripts/workflow/coalescence_network/bpp/example_imap.txt

@@ -0,0 +1,8 @@
+# Example Imap File Template
+# This maps individual sequences to species
+# Format: Individual_ID<tab>Species_Name
+
+ind1	sp1
+ind2	sp2
+ind3	sp3
+ind4	sp4

99.scripts/workflow/coalescence_network/bpp/example_sequences.txt

@@ -0,0 +1,18 @@
+# Example Sequence File Template (PHYLIP format)
+# This is a template - replace with your actual sequence data
+
+# Locus 1
+4 20
+sp1^ind1  ATCGATCGAT CGATCGATCG
+sp2^ind2  ATCGATCGAT CGATCGATCG
+sp3^ind3  ATCGATCGAT CGATCGATCG
+sp4^ind4  ATCGATCGAT CGATCGATCG
+
+# Locus 2
+4 20
+sp1^ind1  CGATCGATCG ATCGATCGAT
+sp2^ind2  CGATCGATCG ATCGATCGAT
+sp3^ind3  CGATCGATCG ATCGATCGAT
+sp4^ind4  CGATCGATCG ATCGATCGAT
+
+# More loci...

99.scripts/workflow/coalescence_network/bpp/generate_and_run_bpp.py

@@ -0,0 +1,251 @@
+#!/usr/bin/env python3
+"""
+Script to generate BPP A00 control file and run BPP analysis.
+
+This script accepts command-line arguments to customize the BPP analysis,
+generates a control file template with the provided parameters,
+and executes the BPP analysis.
+
+Usage:
+    python generate_and_run_bpp.py --seqfile SEQUENCE_FILE \
+                                   --imapfile IMAP_FILE \
+                                   --species SPECIES_NAMES \
+                                   --nloci NUMBER_OF_LOCI \
+                                   --output OUTPUT_NAME \
+                                   --threads THREADS \
+                                   --burnin BURNIN \
+                                   --nsample NSAMPLE \
+                                   --sampfreq SAMPFREQ
+
+Parameters:
+    --seqfile: Path to the sequence file in PHYLIP format
+    --imapfile: Path to the Imap file mapping sequences to species
+    --species: Space-separated list of species names
+    --nloci: Number of loci in the dataset
+    --output: Base name for output files (default: bpp_a00_results)
+    --threads: Number of CPU threads to use (default: 4)
+    --burnin: Number of burn-in iterations for MCMC (default: 10000)
+    --nsample: Number of samples to collect (default: 50000)
+    --sampfreq: Sampling frequency (default: 2)
+    --thetaprior_alpha: Alpha parameter for theta prior (default: 3)
+    --thetaprior_beta: Beta parameter for theta prior (default: 0.002)
+    --tauprior_alpha: Alpha parameter for tau prior (default: 3)
+    --tauprior_beta: Beta parameter for tau prior (default: 0.004)
+"""
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+
+def generate_ctl_file(seqfile, imapfile, species_names, nloci, output_name="bpp_a00_results",
+                      threads=4, burnin=10000, nsample=50000, sampfreq=2,
+                      thetaprior_alpha=3, thetaprior_beta=0.002,
+                      tauprior_alpha=3, tauprior_beta=0.004):
+    """
+    Generate a BPP A00 control file with the specified parameters.
+    
+    Args:
+        seqfile: Path to the sequence file in PHYLIP format
+        imapfile: Path to the Imap file mapping sequences to species
+        species_names: List of species names
+        nloci: Number of loci in the dataset
+        output_name: Base name for output files
+        threads: Number of CPU threads to use
+        burnin: Number of burn-in iterations for MCMC
+        nsample: Number of samples to collect
+        sampfreq: Sampling frequency
+        thetaprior_alpha: Alpha parameter for theta prior
+        thetaprior_beta: Beta parameter for theta prior
+        tauprior_alpha: Alpha parameter for tau prior
+        tauprior_beta: Beta parameter for tau prior
+        
+    Returns:
+        str: Content of the control file
+    """
+    # Convert species names to a space-separated string for the tree
+    species_str = " ".join(species_names)
+    
+    # Create the species count list (all species have 10 individuals in this example)
+    species_counts = " ".join(["10"] * len(species_names))
+    
+    # Create the tree structure (assuming a simple rooted tree)
+    # For a more complex tree, you would need to provide the full Newick format
+    if len(species_names) == 1:
+        tree_str = f"{species_names[0]};"
+    elif len(species_names) == 2:
+        tree_str = f"({species_names[0]}, {species_names[1]});"
+    elif len(species_names) >= 3:
+        # Create a simple nested tree structure
+        # For simplicity, we'll create a tree with the first two species as siblings,
+        # then the rest nested appropriately
+        tree_parts = []
+        for i in range(0, len(species_names), 2):
+            if i + 1 < len(species_names):
+                tree_parts.append(f"({species_names[i]}, {species_names[i+1]})")
+            else:
+                tree_parts.append(species_names[i])
+        
+        # Build the final tree by nesting the parts
+        while len(tree_parts) > 1:
+            left = tree_parts.pop(0)
+            right = tree_parts.pop(0)
+            tree_parts.insert(0, f"({left}, {right})")
+        
+        tree_str = f"{tree_parts[0]};"
+    else:
+        tree_str = "((sp1, sp2), sp3);"
+    
+    # Generate the control file content
+    ctl_content = f"""# BPP A00 Analysis Control File
+# Generated by generate_and_run_bpp.py
+
+seed = -1
+
+# Input files - these are set by the script
+seqfile = {seqfile}
+Imapfile = {imapfile}
+jobname = {output_name}
+
+# Analysis type A00: Fixed species delimitation and fixed species tree
+# Estimate theta and tau parameters on a known tree
+speciesdelimitation = 0    # Fixed species delimitation
+speciestree = 0            # Fixed species tree
+
+# Species tree specification
+# Updated with provided species names, counts, and tree topology
+species&tree = {len(species_names)}  {species_str}
+                  {species_counts}
+                  {tree_str}
+
+# Sequence phasing - set to 1 for unphased diploid data, 0 for phased haploid data
+phase = 0 0 0 0 0
+
+# Use sequence likelihood for inference
+usedata = 1
+
+# Number of loci to analyze - updated with provided value
+nloci = {nloci}
+
+# Clean data option - set to 1 to remove sites with ambiguity characters
+cleandata = 0
+
+# Priors for theta (population size parameters)
+# Inverse gamma prior with alpha={thetaprior_alpha}, beta={thetaprior_beta} (mean={thetaprior_alpha/thetaprior_beta})
+thetaprior = invgamma {thetaprior_alpha} {thetaprior_beta}
+
+# Priors for tau (divergence times)
+# Inverse gamma prior for root tau, Dirichlet for other taus
+tauprior = invgamma {tauprior_alpha} {tauprior_beta}
+
+# Fine-tune MCMC proposals automatically
+finetune = 1
+
+# Output options: MCMC samples, locus rates, heredity scalars, gene trees, substitution parameters
+print = 1 0 0 0 0
+
+# MCMC settings
+burnin = {burnin}      # Burn-in iterations
+sampfreq = {sampfreq}        # Sample every {sampfreq} iterations
+nsample = {nsample}     # Number of samples to collect
+
+# Number of threads to use
+threads = {threads}
+
+# Checkpointing - save progress every 50000 iterations
+checkpoint = 50000 50000
+"""
+    
+    return ctl_content
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Generate BPP A00 control file and run analysis')
+    
+    # Required arguments
+    parser.add_argument('--seqfile', required=True, help='Path to the sequence file in PHYLIP format')
+    parser.add_argument('--imapfile', required=True, help='Path to the Imap file mapping sequences to species')
+    parser.add_argument('--species', nargs='+', required=True, help='Space-separated list of species names')
+    parser.add_argument('--nloci', type=int, required=True, help='Number of loci in the dataset')
+    
+    # Optional arguments with defaults
+    parser.add_argument('--output', default='bpp_a00_results', help='Base name for output files (default: bpp_a00_results)')
+    parser.add_argument('--threads', type=int, default=4, help='Number of CPU threads to use (default: 4)')
+    parser.add_argument('--burnin', type=int, default=10000, help='Number of burn-in iterations for MCMC (default: 10000)')
+    parser.add_argument('--nsample', type=int, default=50000, help='Number of samples to collect (default: 50000)')
+    parser.add_argument('--sampfreq', type=int, default=2, help='Sampling frequency (default: 2)')
+    parser.add_argument('--thetaprior_alpha', type=float, default=3.0, help='Alpha parameter for theta prior (default: 3.0)')
+    parser.add_argument('--thetaprior_beta', type=float, default=0.002, help='Beta parameter for theta prior (default: 0.002)')
+    parser.add_argument('--tauprior_alpha', type=float, default=3.0, help='Alpha parameter for tau prior (default: 3.0)')
+    parser.add_argument('--tauprior_beta', type=float, default=0.004, help='Beta parameter for tau prior (default: 0.004)')
+    
+    args = parser.parse_args()
+    
+    # Validate inputs
+    if not os.path.exists(args.seqfile):
+        print(f"Error: Sequence file '{args.seqfile}' does not exist")
+        sys.exit(1)
+        
+    if not os.path.exists(args.imapfile):
+        print(f"Error: Imap file '{args.imapfile}' does not exist")
+        sys.exit(1)
+        
+    if len(args.species) < 1:
+        print("Error: At least one species name must be provided")
+        sys.exit(1)
+    
+    # Generate the control file content
+    ctl_content = generate_ctl_file(
+        seqfile=args.seqfile,
+        imapfile=args.imapfile,
+        species_names=args.species,
+        nloci=args.nloci,
+        output_name=args.output,
+        threads=args.threads,
+        burnin=args.burnin,
+        nsample=args.nsample,
+        sampfreq=args.sampfreq,
+        thetaprior_alpha=args.thetaprior_alpha,
+        thetaprior_beta=args.thetaprior_beta,
+        tauprior_alpha=args.tauprior_alpha,
+        tauprior_beta=args.tauprior_beta
+    )
+    
+    # Write the control file to disk
+    ctl_filename = f"{args.output}.ctl"
+    with open(ctl_filename, 'w') as f:
+        f.write(ctl_content)
+    
+    print(f"Generated control file: {ctl_filename}")
+    print("\nControl file content:")
+    print("=" * 50)
+    print(ctl_content)
+    print("=" * 50)
+    
+    # Check if BPP is installed
+    if not os.system('which bpp > /dev/null 2>&1') == 0:
+        print("Error: BPP is not installed or not in PATH")
+        print("Please install BPP and make sure it's accessible in your PATH")
+        sys.exit(1)
+    
+    # Run BPP analysis
+    print(f"\nRunning BPP analysis with control file: {ctl_filename}")
+    cmd = f"bpp --cfile {ctl_filename}"
+    print(f"Executing: {cmd}")
+    
+    # Execute the command
+    result = os.system(cmd)
+    
+    if result == 0:
+        print("\nBPP analysis completed successfully!")
+        print(f"Output files:")
+        print(f"  Main output: {args.output}.txt")
+        print(f"  MCMC samples: {args.output}.mcmc.txt")
+    else:
+        print("\nError: BPP analysis failed")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

99.scripts/workflow/coalescence_network/bpp/run_bpp.sh

@@ -0,0 +1,60 @@
+#!/bin/bash
+# Script to run BPP A00 analysis for coalescence network inference
+
+# Set working directory
+WORK_DIR=$(pwd)
+SCRIPT_DIR="$(dirname "$0")"
+
+# Check if BPP is installed and available
+if ! command -v bpp &> /dev/null
+then
+    echo "Error: BPP is not installed or not in PATH"
+    echo "Please install BPP and make sure it's accessible in your PATH"
+    exit 1
+fi
+
+# Check if control file exists
+CONTROL_FILE="${SCRIPT_DIR}/run_bpp_a00.ctl"
+if [ ! -f "$CONTROL_FILE" ]; then
+    echo "Error: Control file not found at $CONTROL_FILE"
+    echo "Please make sure the control file exists"
+    exit 1
+fi
+
+echo "Starting BPP A00 analysis..."
+echo "Control file: $CONTROL_FILE"
+echo "Working directory: $WORK_DIR"
+
+# Run BPP analysis
+bpp --cfile "$CONTROL_FILE"
+
+# Check if the run was successful
+if [ $? -eq 0 ]; then
+    echo "BPP analysis completed successfully!"
+    
+    # Check for output files
+    JOBNAME=$(grep -E "^jobname\s*=" "$CONTROL_FILE" | sed -E 's/^jobname\s*=\s*(.*)/\1/' | tr -d ' ')
+    if [ -z "$JOBNAME" ]; then
+        JOBNAME="out"
+    fi
+    
+    echo "Output files:"
+    echo "  Main output: ${JOBNAME}.txt"
+    echo "  MCMC samples: ${JOBNAME}.mcmc.txt"
+    
+    if [ -f "${JOBNAME}.txt" ]; then
+        echo "Main output file created successfully"
+    else
+        echo "Warning: Main output file not found"
+    fi
+    
+    if [ -f "${JOBNAME}.mcmc.txt" ]; then
+        echo "MCMC samples file created successfully"
+    else
+        echo "Warning: MCMC samples file not found"
+    fi
+    
+else
+    echo "Error: BPP analysis failed"
+    exit 1
+fi

99.scripts/workflow/coalescence_network/bpp/run_bpp_a00.ctl

@@ -0,0 +1,57 @@
+# BPP A00 Analysis Control File
+# For coalescence network analysis with known species tree and delimitation
+
+seed = -1
+
+# Input files - these need to be updated with your actual file paths
+seqfile = sequences.txt
+Imapfile = species_map.txt
+jobname = bpp_a00_results
+
+# Analysis type A00: Fixed species delimitation and fixed species tree
+# Estimate theta and tau parameters on a known tree
+speciesdelimitation = 0    # Fixed species delimitation
+speciestree = 0            # Fixed species tree
+
+# Species tree specification
+# Update the following with your actual species names, counts, and tree topology
+species&tree = 5  sp1  sp2  sp3  sp4  sp5
+                  10   10   10   10   10
+                  ((((sp1, sp2), sp3), sp4), sp5);
+
+# Sequence phasing - set to 1 for unphased diploid data, 0 for phased haploid data
+phase = 0 0 0 0 0
+
+# Use sequence likelihood for inference
+usedata = 1
+
+# Number of loci to analyze - update with your actual number of loci
+nloci = 100
+
+# Clean data option - set to 1 to remove sites with ambiguity characters
+cleandata = 0
+
+# Priors for theta (population size parameters)
+# Inverse gamma prior with alpha=3, beta=0.002 (mean=0.001)
+thetaprior = invgamma 3 0.002
+
+# Priors for tau (divergence times)
+# Inverse gamma prior for root tau, Dirichlet for other taus
+tauprior = invgamma 3 0.004
+
+# Fine-tune MCMC proposals automatically
+finetune = 1
+
+# Output options: MCMC samples, locus rates, heredity scalars, gene trees, substitution parameters
+print = 1 0 0 0 0
+
+# MCMC settings
+burnin = 10000      # Burn-in iterations
+sampfreq = 2        # Sample every 2 iterations
+nsample = 50000     # Number of samples to collect
+
+# Number of threads to use
+threads = 4
+
+# Checkpointing - save progress every 50000 iterations
+checkpoint = 50000 50000

99.scripts_v2/01.prepare_sequences.sh

@@ -0,0 +1,40 @@
+#!/bin/bash
+
+set -euo pipefail
+
+cd "$PROJECTHOME"/11.reference_v2
+
+# HG sequences name should be changed.
+cd raw
+seqkit replace -k HG.map.txt -p "^(\S+).*$" -r "{kv}" GCA_030763125.1_ASM3076312v1_genomic.fna -o HG.fa -K --f-use-regexp
+
+# MG & ZG use hapA genome
+grep -Fwf MG.target.txt MG.gff > MG.target.gff
+grep -Fwf ZG.target.txt ZG.gff > ZG.target.gff
+
+# Extract CDS sequences from GFF3 files using gffread
+pueue add -- gffread -g raw/HN.fa -x HN.cds.fa -y HN.pep.fa raw/HN.gff3
+pueue add -- gffread -g raw/HG.fa -x HG.cds.fa -y HG.pep.fa raw/Hippophae_gyantsensis.gff
+pueue add -- gffread -g raw/HS.fa -x HS.cds.fa -y HS.pep.fa raw/HS.gff3
+pueue add -- gffread -g raw/YN.genome.fa -x YN.cds.fa -y YN.pep.fa raw/YN.gff3
+pueue add -- gffread -g raw/ZG.genome.fa -x ZG.cds.fa -y ZG.pep.fa raw/ZG.target.gff
+pueue add -- gffread -g raw/ZJ.genome.fa -x ZJ.cds.fa -y ZJ.pep.fa raw/ZJ.gff
+pueue add -- gffread -g raw/ZY.fa -x ZY.cds.fa -y ZY.pep.fa raw/ZY.gff3
+pueue add -- gffread -g raw/Hippophae_tibetana.genomic.fasta -x HT.cds.fa -y HT.pep.fa raw/Hippophae_tibetana.mRNA.gff
+pueue add -- gffread -g raw/MG.genome.fasta -x MG.cds.fa -y MG.pep.fa raw/MG.target.gff
+cp raw/EA.gff3.cds EA.cds.fa
+cp raw/EM.genome.cds.fasta EM.cds.fa
+cp raw/EA.gff3.pep EA.pep.fa
+cp raw/EM.pep.fasta EM.pep.fa
+
+mkdir pep
+mkdir cds
+mv ./*.cds.fa cds
+mv ./*.pep.fa pep
+
+cd pep
+primary_transcript ./ last_dot
+
+# EM基因命名特殊性，导致直接使用primary_transcript会出现问题，直接复制即可
+cp EM.pep.fa primary_transcripts/EM.pep.fa
+

99.scripts_v2/02.orthofinder.sh

@@ -0,0 +1,21 @@
+# prepare input files for orthofinder
+mkdir input_pep
+cp ../11.reference_v2/pep/primary_transcripts/*.pep.fa input_pep
+mkdir input_pep/core
+mkdir input_pep/outgroup
+mv input_pep/EA.pep.fa input_pep/outgroup
+mv input_pep/EM.pep.fa input_pep/outgroup
+mv input_pep/ZJ.pep.fa input_pep/outgroup
+mv input_pep/*.pep.fa input_pep/core
+for i in input_pep/*/*.pep.fa; do
+    base=$(basename "$i" .pep.fa)
+    echo "Processing $base"
+    sed -i "s/>/>${base}@/g" "$i"
+done
+
+# run orthofinder with Hippophae genomes as backbone
+pueue add -- orthofinder -t 12 -a 4 -f input_pep/core -o orthofinder_out
+
+# assign outgroups
+pueue add -- orthofinder -t 12 -a 4 --assign input_pep/outgroup --core orthofinder_out/Results_Hippophae_only
+

pixi.toml

@@ -1,9 +1,9 @@
 [workspace]
 authors = ["IvisTang <me@ivistang.com>"]
 channels = [
-    "https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/",
+    "https://mirrors4.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/",
-    "https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bioconda/",
+    "https://mirrors4.tuna.tsinghua.edu.cn/anaconda/cloud/bioconda/",
-    "conda-forge", 
+    "conda-forge",
     "bioconda"
 ]
 name = "biyelunwen"
@@ -61,6 +61,15 @@ r-processx = ">=3.8.6,<4"
 beagle-lib = ">=4.0.1,<5"
 beast = ">=10.5.0,<11"
 
+[feature.genome.dependencies]
+gffread = ">=0.12.9,<0.13"
+orthofinder = ">=3.1.5,<4"
+seqkit = ">=2.13.0,<3"
+tmux = ">=3.7b_,<4"
+numpy = "<2"
+
+
 [environments]
-default = ["base"]
+base = ["base"]
 beast = ["beast"]
+default = ["genome"]