Added simple autocycler_wrapper helper script

scripts/autocycler_wrapper.sh

@@ -0,0 +1,70 @@
+#!/usr/bin/env bash
+
+# Command line wrapper for autocycler.
+# Usage:
+#   autocycler_wrapper.sh <reads> <output_folder> <read_partitions> <threads> 
+#
+# Example usage:
+#   autocycler_wrapper.sh ont.fastq.gz output_autocycler 4 16
+#
+# The example  runs  autocycler on the reads 'ont.fastq.gz' and
+# outputs everything into the folder 'output_autocycler'.
+# It divides the reads into 4 partitions and uses 16 threads.
+
+reads=$1  # Your read set goes here
+output=$2  # Name you output folder here
+subset=$3  # Number of read subset partitions (default is 4. Auto-prefixes 0 for any number below 10)
+threads=$4  # set as appropriate for your system
+
+# Add 0 prefix for read sub-sets if lower than 10
+if [ "${#1}" -lt "2" ]; then
+    subset="0${subset}"
+fi
+
+# Input parameter print
+echo Running autocycler with following parameters\:
+echo Reads\: $reads
+echo Output folder\: $output
+echo Read partitions\: $subset
+echo Threads\: $threads
+mkdir -p $output
+
+# Estimate genome size: Use lrge if it is installed, otherwise use the slower bundled Raven estimator
+echo -e "\nEstimating genome size:"
+if ! command -v lrge 2>&1 >/dev/null
+then
+    genome_size=$(genome_size_raven.sh "$reads" "$threads")
+else
+    genome_size=$(lrge -t "$threads" "$reads")
+fi
+
+# Step 1: subsample the long-read set into multiple files
+autocycler subsample --count $subset  --reads "$reads" --out_dir ${output}/subsampled_reads --genome_size "$genome_size"
+
+# Step 2: assemble each subsampled file
+mkdir -p $output/assemblies
+for assembler in canu flye miniasm necat nextdenovo raven; do
+    for i in `eval echo {01..$subset}`; do
+        "$assembler".sh ${output}/subsampled_reads/sample_"$i".fastq ${output}/assemblies/"$assembler"_"$i" "$threads" "$genome_size"
+    done
+done
+
+# Optional step: remove the subsampled reads to save space
+rm ${output}/subsampled_reads/*.fastq
+
+# Step 3: compress the input assemblies into a unitig graph
+autocycler compress -i ${output}/assemblies -a ${output}/autocycler_out
+
+# Step 4: cluster the input contigs into putative genomic sequences
+autocycler cluster -a ${output}/autocycler_out
+
+# Steps 5 and 6: trim and resolve each QC-pass cluster
+for c in ${output}/autocycler_out/clustering/qc_pass/cluster_*; do
+    autocycler trim -c "$c"
+    autocycler resolve -c "$c"
+done
+
+# Step 7: combine resolved clusters into a final assembly
+echo Running Autocycler combine
+autocycler combine -a ${output}/autocycler_out -i ${output}/autocycler_out/clustering/qc_pass/cluster_*/5_final.gfa
+

scripts/environment.yml

@@ -4,9 +4,9 @@ channels:
   - bioconda
 dependencies:
   - any2fasta>=0.4.2             # https://github.com/tseemann/any2fasta
-  - canu>=2.2                    # https://github.com/marbl/canu
+  - canu>=2.3                    # https://github.com/marbl/canu
   - flye>=2.9.5                  # https://github.com/mikolmogorov/Flye
-  - lja>=0.2                     # https://github.com/AntonBankevich/LJA
+#  - lja>=0.2                     # https://github.com/AntonBankevich/LJA
   - metamdbg>=1.0                # https://github.com/GaetanBenoitDev/metaMDBG
   - miniasm>=0.3                 # https://github.com/lh3/miniasm
   - minimap2>=2.28               # https://github.com/lh3/minimap2