For completeness sake, I wanted to create an additional C.bairdi transcriptome assembly that consisted of Arthropoda only sequences from just pooled RNAseq data (since I recently generated a similar assembly without taxonomically filtered reads on 20200518). This constitutes samples we have designated: 2018, 2019, 2020-UW. A de novo assembly was run using Trinity on Mox. Since all pooled RNAseq libraries were stranded, I added this option to Trinity command.
The resulting assembly will be referred to as:
cbai_transcriptome_v1.7.fasta
SBATCH script (GitHub):
#!/bin/bash
## Job Name
#SBATCH --job-name=trinity_cbai_v1.7
## Allocation Definition
#SBATCH --account=srlab
#SBATCH --partition=srlab
## Resources
## Nodes
#SBATCH --nodes=1
## Walltime (days-hours:minutes:seconds format)
#SBATCH --time=9-00:00:00
## Memory per node
#SBATCH --mem=500G
##turn on e-mail notification
#SBATCH --mail-type=ALL
#SBATCH --mail-user=samwhite@uw.edu
## Specify the working directory for this job
#SBATCH --chdir=/gscratch/scrubbed/samwhite/outputs/20200527_cbai_trinity_arthropoda_pooled_RNAseq
### Trinity de novo assembly of all pooled C.bairdi Arthropoda-only RNAseq data.
### Includes "descriptor_1" short-hand of: 2020-UW, 2019, 2018.
### See fastq.list.txt file for list of input files used for assembly.
# Exit script if a command fails
set -e
# Load Python Mox module for Python module availability
module load intel-python3_2017
# Document programs in PATH (primarily for program version ID)
{
date
echo ""
echo "System PATH for $SLURM_JOB_ID"
echo ""
printf "%0.s-" {1..10}
echo "${PATH}" | tr : \\n
} >> system_path.log
# User-defined variables
reads_dir=/gscratch/srlab/sam/data/C_bairdi/RNAseq
transcriptome_dir=/gscratch/srlab/sam/data/C_bairdi/transcriptomes
threads=28
assembly_stats=assembly_stats.txt
fasta_name="cbai_transcriptome_v1.7.fasta"
# Paths to programs
trinity_dir="/gscratch/srlab/programs/trinityrnaseq-v2.9.0"
samtools="/gscratch/srlab/programs/samtools-1.10/samtools"
## Inititalize arrays
R1_array=()
R2_array=()
# Variables for R1/R2 lists
R1_list=""
R2_list=""
# Create array of fastq R1 files
R1_array=("${reads_dir}"/*3[80][804]*R1.fq)
# Create array of fastq R2 files
R2_array=("${reads_dir}"/*3[80][804]*R2.fq)
# Create list of fastq files used in analysis
## Uses parameter substitution to strip leading path from filename
for fastq in "${reads_dir}"/*3[80][804]*.fq
do
echo "${fastq##*/}" >> fastq.list.txt
done
# Create comma-separated lists of FastQ reads
R1_list=$(echo "${R1_array[@]}" | tr " " ",")
R2_list=$(echo "${R2_array[@]}" | tr " " ",")
# Run Trinity
${trinity_dir}/Trinity \
--seqType fq \
--max_memory 500G \
--CPU ${threads} \
--SS_lib_type RF \
--left "${R1_list}" \
--right "${R2_list}"
# Rename generic assembly FastA
mv trinity_out_dir/Trinity.fasta trinity_out_dir/"${fasta_name}"
# Assembly stats
${trinity_dir}/util/TrinityStats.pl trinity_out_dir/"${fasta_name}" \
> ${assembly_stats}
# Create gene map files
${trinity_dir}/util/support_scripts/get_Trinity_gene_to_trans_map.pl \
trinity_out_dir/"${fasta_name}" \
> trinity_out_dir/"${fasta_name}".gene_trans_map
# Create sequence lengths file (used for differential gene expression)
${trinity_dir}/util/misc/fasta_seq_length.pl \
trinity_out_dir/"${fasta_name}" \
> trinity_out_dir/"${fasta_name}".seq_lens
# Create FastA index
${samtools} faidx \
trinity_out_dir/"${fasta_name}"
# Copy files to transcriptome directory
rsync -av \
trinity_out_dir/"${fasta_name}"* \
${transcriptome_dir}
# Generate FastA MD5 checksum
# See last line of SLURM output file
cd trinity_out_dir
md5sum "${fasta_name}" > "${fasta_name}".checksum.md5
RESULTS
Remarkably quick; only ~1.5hrs:
Output folder:
Input FastQ list (text):
FastA (412MB):
-
- MD5 =
032d1f81c7744736ebeefe7f63ed6d95
- MD5 =
FastA Index (text):
The following sets of files are useful for downstream gene expression and annotation using Trinity.
Trinity FastA Gene Trans Map (text):
Trinity FastA Sequence Lengths (text):
Assembly stats (text):
################################
## Counts of transcripts, etc.
################################
Total trinity 'genes': 14225
Total trinity transcripts: 20526
Percent GC: 53.57
########################################
Stats based on ALL transcript contigs:
########################################
Contig N10: 3760
Contig N20: 2713
Contig N30: 2122
Contig N40: 1777
Contig N50: 1504
Median contig length: 777
Average contig: 1053.71
Total assembled bases: 21628372
#####################################################
## Stats based on ONLY LONGEST ISOFORM per 'GENE':
#####################################################
Contig N10: 3373
Contig N20: 2449
Contig N30: 1958
Contig N40: 1645
Contig N50: 1371
Median contig length: 659
Average contig: 930.99
Total assembled bases: 13243346