Based on a discussion in this GitHub Issue, I’ve initiated some tissue-specific transcriptome assemblies with our current geoduck data.

Job was run on Mox and rsynced to my folder on Gannet.

FastA index files were generated separately via samtools faidx Trinity.fasta (didn’t think about it at the time so did not add to SBATCH script).

SBATCH script:

20190215_geo_trinity_juvD5.sh(GitHub)


#!/bin/bash
## Job Name
#SBATCH --job-name=trinity_20190215
## Allocation Definition
#SBATCH --account=coenv
#SBATCH --partition=coenv
## Resources
## Nodes
#SBATCH --nodes=2
## Walltime (days-hours:minutes:seconds format)
#SBATCH --time=5-00:00:00
## Memory per node
#SBATCH --mem=120G
##turn on e-mail notification
#SBATCH --mail-type=ALL
#SBATCH --mail-user=samwhite@uw.edu
## Specify the working directory for this job
#SBATCH --workdir=/gscratch/scrubbed/samwhite/outputs/20190215_trinity_geoduck_juvD5_RNAseq

# Load Python Mox module for Python module availability

module load intel-python3_2017

# Document programs in PATH (primarily for program version ID)

date >> system_path.log
echo "" >> system_path.log
echo "System PATH for $SLURM_JOB_ID" >> system_path.log
echo "" >> system_path.log
printf "%0.s-" {1..10} >> system_path.log
echo ${PATH} | tr : \\n >> system_path.log

data_dir=/gscratch/scrubbed/samwhite/data/P_generosa/RNAseq
trinity_dir=/gscratch/srlab/programs/Trinity-v2.8.3
assembly_stats=assembly_stats.txt

# Run Trinity
${trinity_dir}/Trinity \
--trimmomatic \
--seqType fq \
--max_memory 120G \
--CPU 56 \
--left \
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-1_S8_L001_R1_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-2_S16_L002_R1_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-3_S24_L003_R1_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-4_S32_L004_R1_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-5_S40_L005_R1_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-6_S48_L006_R1_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-7_S56_L007_R1_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-8_S64_L008_R1_001.fastq.gz \
--right \
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-1_S8_L001_R2_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-2_S16_L002_R2_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-3_S24_L003_R2_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-4_S32_L004_R2_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-5_S40_L005_R2_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-6_S48_L006_R2_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-7_S56_L007_R2_001.fastq.gz,\
${data_dir}/Geoduck-larvae-day5-RNA-EPI-99-8_S64_L008_R2_001.fastq.gz

# Assembly stats
${trinity_dir}/util/TrinityStats.pl trinity_out_dir/Trinity.fasta \
> ${assembly_stats}

RESULTS

Output folder:

20190215_trinity_geoduck_juvD5_RNAseq/

Trinity assembly:

20190215_trinity_geoduck_juvD5_RNAseq/trinity_out_dir/Trinity.fasta(FastA)
- FastA index (samtools faidx):
  - 20190215_trinity_geoduck_juvD5_RNAseq/trinity_out_dir/Trinity.fasta.fai

Assembly stats:

20190215_trinity_geoduck_juvD5_RNAseq/assembly_stats.txt




################################
## Counts of transcripts, etc.
################################
Total trinity 'genes':  235162
Total trinity transcripts:  402320
Percent GC: 36.64

########################################
Stats based on ALL transcript contigs:
########################################

    Contig N10: 4323
    Contig N20: 2946
    Contig N30: 2166
    Contig N40: 1619
    Contig N50: 1189

    Median contig length: 388
    Average contig: 722.92
    Total assembled bases: 290845329


#####################################################
## Stats based on ONLY LONGEST ISOFORM per 'GENE':
#####################################################

    Contig N10: 3483
    Contig N20: 2214
    Contig N30: 1523
    Contig N40: 1057
    Contig N50: 733

    Median contig length: 316
    Average contig: 549.73
    Total assembled bases: 129274787

Will likely run the resulting assembly through Trinnotate and Transdecoder to try to get a more refined assembly.

Will also run BUSCO on the refined assembly to evaluate its completeness.

Will also explore combining all of the geoduck tissue-specific transcriptome assemblies using DRAP (mentioned/suggested by Katherine in that GitHub issue).