...
As genome assembly is important part of analysis but is building a reference file that will be used many times, it makes more sense to install it its own environment. Other potential tools to have in the same environment would be read preprocessing tools, in particular adapter removal tools such as trimmomatic.
| Code Block | ||
|---|---|---|
| ||
conda create --name GVA-SPAdes -c bioconda spades |
Testing SPAdes installation
...
| Line number | As is | To be |
|---|---|---|
| 16 | #SBATCH -J jobName | #SBATCH -J spades |
| 17 | #SBATCH -n 1 | #SBATCH -n 4 |
| 18 | #SBATCH -N 1 | #SBATCH -N 4 |
| 21 | #SBATCH -t 12:00:00 | #SBATCH -t 104:0030:00 |
| 22 | ##SBATCH --mail-user=ADD | #SBATCH --mail-user=<YourEmailAddress> |
| 23 | ##SBATCH --mail-type=all | #SBATCH --mail-type=all |
| 27 | conda activate GVA2021 | conda activate GVA-SPAdes |
| 31 | export LAUNCHER_JOB_FILE=commands | export LAUNCHER_JOB_FILE=spades_commands |
...
| Code Block | ||||
|---|---|---|---|---|
| ||||
# Count the total number of contigs: grep -c "^>" single_end/contigs.fasta # Determine the length of the 5 largest contigs: grep "^>" single_end/contigs.fasta | head -n 5 # Determine the length of the 20 smallest contigs: grep "^>" single_end/contigs.fasta | tail -n 20 # Determine the length of the 100th through 110th contigs: grep "^>" single_end/contigs.fasta | head -n 110 | tail -n 10 |
If Since you ran multiple different combinations of reads for the simulated data how did the insert size effect the number of contigs? the length of the largest contigs? Why might larger insert sizes not help things very much?
...