Transcriptome Assembly - Hematodinium with MEGAN6 Taxonomy-specific Reads with Trinity on Mox

2020
Miscellaneous
Author

Sam White

Published

January 22, 2020

Ran a de novo assembly using the extracted reads classified under Alveolata from 20200122 The assembly was performed with Trinity on Mox.

For reference, these include RNAseq data using a newly established “shorthand”: 2018, 2019.

SBATCH script (GitHub):

#!/bin/bash
## Job Name
#SBATCH --job-name=trinity_hemat
## Allocation Definition
#SBATCH --account=srlab
#SBATCH --partition=srlab
## Resources
## Nodes
#SBATCH --nodes=1
## Walltime (days-hours:minutes:seconds format)
#SBATCH --time=10-00:00:00
## 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 --chdir=/gscratch/scrubbed/samwhite/outputs/20200122_hemat_trinity_megan_RNAseq

# 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
threads=27
assembly_stats=assembly_stats.txt
timestamp=$(date +%Y%m%d)
fasta_name="${timestamp}.hemat.megan.Trinity.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}/*_R1.fq)

# Create array of fastq R2 files
R2_array=(${reads_dir}/*_R2.fq)

# Create list of fastq files used in analysis
## Uses parameter substitution to strip leading path from filename
for fastq in ${reads_dir}/*.fq
do
  echo "${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 using "stranded" setting (--SS_lib_type)
${trinity_dir}/Trinity \
--seqType fq \
--max_memory 120G \
--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 FastA index
${samtools} faidx \
trinity_out_dir/${fasta_name}

RESULTS

This was quick, ~11 minutes:

Trinity runtime for hematodinium assembly

Output folder:

Assembly (FastA; 20MB):

FastA Index (FAI):

Trinity Gene Trans Map (txt):

Assembly Stats (txt):



################################
## Counts of transcripts, etc.
################################
Total trinity 'genes':  4440
Total trinity transcripts:  5183
Percent GC: 50.21

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

    Contig N10: 1856
    Contig N20: 1446
    Contig N30: 1189
    Contig N40: 1000
    Contig N50: 870

    Median contig length: 634
    Average contig: 736.61
    Total assembled bases: 3817832


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

    Contig N10: 1803
    Contig N20: 1422
    Contig N30: 1175
    Contig N40: 986
    Contig N50: 848

    Median contig length: 612
    Average contig: 713.35
    Total assembled bases: 3167294