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Annotated aTRAM workflow.txt
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Annotated aTRAM workflow.txt
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# Directory set up
# In the working directory create a subdirectory for this set of experiments
#
mkdir "DATE"_WGS_data
#
#
# Enter the subdirectory
cd "DATE"_WGS_data
#
#
# Create a subdirectory for the sample to be analyzed
#
mkdir "SAMPLE_NAME"
#
# enter the sample subdirectory
#
cd "SAMPLE_NAME"
#
# Upload WGS fastq files (Read 1 and Read 2) for the sample to its appropriate directory
# This step was done using a free FTP program like FileZilla
#
# Create an aTRAM directory for the output files
mkdir "path to working directory"/atram_db
#
#
# Set your path variables
export PATH=$PATH:"path to SPAdes"/SPAdes-3.15.3-Linux/bin
export PATH=$PATH:"path to ncbi blast"/ncbi-blast-2.12.0+/bin
#
#
# Direct temporary files to a directory with sufficient space
# (files are automatically removed when the run is complete)
#
export SQLITE_TMPDIR="path to working directory"/atram_db/temp_files
#
#
# Remove the sequencing adapters
# "WGSadapt.fasta" contains platform specific sequencing adapters
# Using default/recommended parameters from trimmomatic
#
trimmomatic PE -phred33 "SAMPLE_NAME"_"RUN_and_FLOW_CELL_information"_1.clean.fq.gz "SAMPLE_NAME"_"RUN_and_FLOW_CELL_information"_2.clean.fq.gz "SAMPLE_NAME"_forward_paired.fq.gz "SAMPLE_NAME"_forward_unpaired.fq.gz "SAMPLE_NAME"_reverse_paired.fq.gz "SAMPLE_NAME"_reverse_unpaired.fq.gz ILLUMINACLIP:"path to fasta file with adapter sequences"/WGSadapt.fasta:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36
#
#
# Preparing the library
# aTRAM is building BLAST databases and an SQLite3 database for rapid read retrieval
# "python3" specifies which version of python to use if multiple are installed
# --cpus specifies the number of computer cores to use
# "SAMPLE_LIBRARY" specifies the prefix/name for the library being built
# -t specifies location of temp files if different from default
#
python3 "path_to_aTRAM_package"/aTRAM/atram_preprocessor.py --cpus 8 --blast-db "path to working directory"/atram_db/"SAMPLE_LIBRARY" --end-1 "path to working directory"/"DATE"_WGS_data/"SAMPLE_NAME"/"SAMPLE_NAME"_forward_paired.fq.gz --end-2 "path to working directory"/"DATE"_WGS_data/"SAMPLE_NAME"/"SAMPLE_NAME"_reverse_paired.fq.gz -t "path to working directory"/atram_db/temp_files
#
# Assembling Loci
# aTRAM searches the databases built in the previous step for the sequence of interest
# "python3" specifies which version of python to use if multiple are installed
# --cpus specifies the number of computer cores to use
# "TRANSGENE_SEQUENCE".fasta contains the sequence of interest (the transgene) in fasta format
# -a specifies which assembler is being used
# -i specifies how many iterations/successive searches should be performed
#
python3 /usr/local/bin/aTRAM/atram.py --cpus 8 --blast-db "path to working directory"/atram_db/"SAMPLE_LIBRARY" \
-Q "path to working directory"/"DATE"_WGS_data/"TRANSGENE_SEQUENCE".fasta \
-o "path to working directory"/"DATE"_WGS_data/"SAMPLE_NAME"/"SAMPLE_NAME".fasta \
--log-file "path to working directory"/"DATE"_WGS_data/"SAMPLE_NAME"/"SAMPLE_NAME".log -a spades -i 20