Run RNAseq on perkinsus datasets

This is a meta analysis of 4 RNAseq datasets each comparing different oysters infected with Perkinsus marinus.

I first got all the meta data from the SRA Run Selector (e.g. https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRP301630) I downloaded this csv file by clicking the ‘Metadata’ button under the download heading.

I then got lists of accessions and concatenated them into one list (ids.csv) to be fed to the FetchNGS pipeine.

Then I ran FetchNGS to get all the datasets

FetchNGS

# create a screen session
screen -S nextflow

# request a compute node (mem and time requests can be modified)
salloc -A srlab -p cpu-g2-mem2x -N 1 -c 1 --mem=16GB --time=12:00:00

# load the nextflow environment
mamba activate nextflow

# run nextflow pipeline
nextflow run \
nf-core/fetchngs \
-resume \
-c /gscratch/srlab/strigg/bin/uw_hyak_srlab.config \
--input /gscratch/scrubbed/strigg/analyses/20241104_RNAseq/ids.csv \
--outdir /gscratch/scrubbed/strigg/analyses/20241104_RNAseq \
--download_method sratools

11/08/2024
I ended up canceling the job (CTRL + c) because it was taking too long to run. It seemed stalled out:

nextflow.log file
trace file
timeline report
summary report: note it says completed even though I did CTRL + c
I exited the screen session as follows
```
screen -XS nextflow quit
```

I reran the job in a new screen session and new directory (20241108_FetchNGS).

# create a screen session
screen -S nextflow

# request a compute node (mem and time requests can be modified)
salloc -A srlab -p cpu-g2-mem2x -N 1 -c 1 --mem=16GB --time=12:00:00

# load the nextflow environment
mamba activate nextflow

# run nextflow pipeline
nextflow run \
nf-core/fetchngs \
-resume \
-c /gscratch/srlab/strigg/bin/uw_hyak_srlab.config \
--input /gscratch/scrubbed/strigg/analyses/20241104_RNAseq/ids.csv \
--outdir /gscratch/scrubbed/strigg/analyses/20241108_RNAseq \
--download_method sratools

It completed in 1.5 hours which is crazy fast. .