How to extract fastq files from SRA

geofetch --version
geofetch 0.12.4

1) Download SRA files and PEP using GEOfetch

Add flags: a) --add-convert-modifier (To add looper configurations for conversion) b) --discard-soft (To delete soft files. We don't need them :D)

geofetch -i GSE67303 -n red_algae -m `pwd` --add-convert-modifier --discard-soft
Metadata folder: /home/bnt4me/virginia/repos/geofetch/docs_jupyter/red_algae
Trying GSE67303 (not a file) as accession...
Skipped 0 accessions. Starting now.
Processing accession 1 of 1: 'GSE67303'
Processed 4 samples.
Expanding metadata list...
Found SRA Project accession: SRP056574
Downloading SRP056574 sra metadata
Parsing SRA file to download SRR records
Getting SRR: SRR1930183  in (GSE67303)

2023-08-01T17:04:12 prefetch.2.11.3: Current preference is set to retrieve SRA Normalized Format files with full base quality scores.
2023-08-01T17:04:12 prefetch.2.11.3: 1) Downloading 'SRR1930183'...
2023-08-01T17:04:12 prefetch.2.11.3: SRA Normalized Format file is being retrieved, if this is different from your preference, it may be due to current file availability.
2023-08-01T17:04:12 prefetch.2.11.3:  Downloading via HTTPS...
2023-08-01T17:04:14 prefetch.2.11.3:  HTTPS download succeed
2023-08-01T17:04:15 prefetch.2.11.3:  'SRR1930183' is valid
2023-08-01T17:04:15 prefetch.2.11.3: 1) 'SRR1930183' was downloaded successfully
2023-08-01T17:04:15 prefetch.2.11.3: 'SRR1930183' has 0 unresolved dependencies
Getting SRR: SRR1930184  in (GSE67303)

2023-08-01T17:04:15 prefetch.2.11.3: Current preference is set to retrieve SRA Normalized Format files with full base quality scores.
2023-08-01T17:04:16 prefetch.2.11.3: 1) Downloading 'SRR1930184'...
2023-08-01T17:04:16 prefetch.2.11.3: SRA Normalized Format file is being retrieved, if this is different from your preference, it may be due to current file availability.
2023-08-01T17:04:16 prefetch.2.11.3:  Downloading via HTTPS...
2023-08-01T17:04:17 prefetch.2.11.3:  HTTPS download succeed
2023-08-01T17:04:18 prefetch.2.11.3:  'SRR1930184' is valid
2023-08-01T17:04:18 prefetch.2.11.3: 1) 'SRR1930184' was downloaded successfully
2023-08-01T17:04:18 prefetch.2.11.3: 'SRR1930184' has 0 unresolved dependencies
Getting SRR: SRR1930185  in (GSE67303)

2023-08-01T17:04:19 prefetch.2.11.3: Current preference is set to retrieve SRA Normalized Format files with full base quality scores.
2023-08-01T17:04:19 prefetch.2.11.3: 1) Downloading 'SRR1930185'...
2023-08-01T17:04:19 prefetch.2.11.3: SRA Normalized Format file is being retrieved, if this is different from your preference, it may be due to current file availability.
2023-08-01T17:04:19 prefetch.2.11.3:  Downloading via HTTPS...
2023-08-01T17:04:22 prefetch.2.11.3:  HTTPS download succeed
2023-08-01T17:04:22 prefetch.2.11.3:  'SRR1930185' is valid
2023-08-01T17:04:22 prefetch.2.11.3: 1) 'SRR1930185' was downloaded successfully
2023-08-01T17:04:22 prefetch.2.11.3: 'SRR1930185' has 0 unresolved dependencies
Getting SRR: SRR1930186  in (GSE67303)

2023-08-01T17:04:22 prefetch.2.11.3: Current preference is set to retrieve SRA Normalized Format files with full base quality scores.
2023-08-01T17:04:23 prefetch.2.11.3: 1) Downloading 'SRR1930186'...
2023-08-01T17:04:23 prefetch.2.11.3: SRA Normalized Format file is being retrieved, if this is different from your preference, it may be due to current file availability.
2023-08-01T17:04:23 prefetch.2.11.3:  Downloading via HTTPS...
2023-08-01T17:04:25 prefetch.2.11.3:  HTTPS download succeed
2023-08-01T17:04:25 prefetch.2.11.3:  'SRR1930186' is valid
2023-08-01T17:04:25 prefetch.2.11.3: 1) 'SRR1930186' was downloaded successfully
2023-08-01T17:04:25 prefetch.2.11.3: 'SRR1930186' has 0 unresolved dependencies
Finished processing 1 accession(s)
Cleaning soft files ...
Creating complete project annotation sheets and config file...
Sample annotation sheet: /home/bnt4me/virginia/repos/geofetch/docs_jupyter/red_algae/GSE67303_PEP/GSE67303_PEP_raw.csv . Saved!
File has been saved successfully
  Config file: /home/bnt4me/virginia/repos/geofetch/docs_jupyter/red_algae/GSE67303_PEP/GSE67303_PEP.yaml

Let's see if files were downloaded:

ls
build                             python-usage.ipynb          SRR1930184
code                              raw-data-downloading.ipynb  SRR1930185
how_to_fastq_from_sra.ipynb       red_algae                   SRR1930186
processed-data-downloading.ipynb  SRR1930183

now let's check how does our config file looks like:

cat ./red_algae/GSE67303_PEP/GSE67303_PEP.yaml
# Autogenerated by geofetch

name: GSE67303
pep_version: 2.1.0
sample_table: GSE67303_PEP_raw.csv

"experiment_metadata":
  "series_contact_address": "930 N University Ave"
  "series_contact_city": "Ann Arbor"
  "series_contact_country": "USA"
  "series_contact_department": "Chemistry"
  "series_contact_email": "[email protected]"
  "series_contact_institute": "University of Michigan"
  "series_contact_laboratory": "Koutmou Lab"
  "series_contact_name": "mehmet,,tardu"
  "series_contact_state": "MI"
  "series_contact_zip_postal_code": "48109"
  "series_contributor": "Mehmet,,Tardu + Ugur,M,Dikbas + Ibrahim,,Baris + Ibrahim,H,Kavakli"
  "series_geo_accession": "GSE67303"
  "series_last_update_date": "May 15 2019"
  "series_overall_design": "Identification of blue light and red light regulated genes\
    \ by deep sequencing in biological duplicates. qRT-PCR was performed to verify\
    \ the RNA-seq results."
  "series_platform_id": "GPL19949"
  "series_platform_organism": "Cyanidioschyzon merolae strain 10D"
  "series_platform_taxid": "280699"
  "series_pubmed_id": "27614431"
  "series_relation": "BioProject: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA279462\
    \ + SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRP056574"
  "series_sample_id": "GSM1644066 + GSM1644067 + GSM1644068 + GSM1644069"
  "series_sample_organism": "Cyanidioschyzon merolae strain 10D"
  "series_sample_taxid": "280699"
  "series_status": "Public on Sep 01 2016"
  "series_submission_date": "Mar 26 2015"
  "series_summary": "Light is one of the main environmental cues that affects the\
    \ physiology and behavior of many organisms. The effect of light on genome-wide\
    \ transcriptional regulation has been well-studied in green algae and plants,\
    \ but not in red algae. Cyanidioschyzon merolae is used as a model red algae,\
    \ and is suitable for studies on transcriptomics because of its compact genome\
    \ with a relatively small number of genes. In addition, complete genome sequences\
    \ of the nucleus, mitochondrion, and chloroplast of this organism have been determined.\
    \ Together, these attributes make C. merolae an ideal model organism to study\
    \ the response to light stimuli at the transcriptional and the systems biology\
    \ levels. Previous studies have shown that light significantly affects cell signaling\
    \ in this organism, but there are no reports on its blue light- and red light-mediated\
    \ transcriptional responses. We investigated the direct effects of blue and red\
    \ light at the transcriptional level using RNA-seq. Blue and red light were found\
    \ to regulate 35% of the total genes in C. merolae. Blue light affected the transcription\
    \ of genes involved protein synthesis while red light specifically regulated the\
    \ transcription of genes involved in photosynthesis and DNA repair. Blue or red\
    \ light regulated genes involved in carbon metabolism and pigment biosynthesis.\
    \ Overall, our data showed that red and blue light regulate the majority of the\
    \ cellular, cell division, and repair processes in C. merolae."
  "series_supplementary_file": "ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE67nnn/GSE67303/suppl/GSE67303_DEG_cuffdiff.xlsx"
  "series_title": "RNA-seq analysis of the transcriptional response to blue and red\
    \ light in the extremophilic red alga, Cyanidioschyzon merolae"
  "series_type": "Expression profiling by high throughput sequencing"



sample_modifiers:
  append:
    # Project metadata:
    sample_treatment_protocol_ch1: "Cells were exposed to blue-light (15 ┬Ámole m-2s-1) for 30 minutes"
    sample_growth_protocol_ch1: "Cyanidioschyzon merolae cells were grown in 2xMA media"
    sample_extract_protocol_ch1: "Dark kept and blue-light exposed C.merolae cells were removed and RNA was harvested using Trizol reagent. Illumina TruSeq RNA Sample Prep Kit (Cat#RS-122-2001) was used with 1 ug of total RNA for the construction of sequencing libraries., RNA libraries were prepared for sequencing using standard Illumina protocols"
    sample_data_processing: "The purified cDNA library was sequenced on Illumina''s MiSeq sequencing platform following vendor''s instruction for running the instrument., Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to Cyanidioschyzon merolae 10D reference genome (assembly ID:ASM9120v1) using TopHat (v2.0.5)., Differential expression analysis was conducted by using cuffdiff tool in cufflink suite (v2.2)"
    supplementary_files_format_and_content: "Excel spreadsheet includes FPKM values for Darkness and Blue-Light exposed samples with p and q values of cuffdiff output."
    # End of project metadata


    # Adding sra convert looper pipeline
    SRR_files: SRA

  derive:
    attributes: [read1, read2, SRR_files]
    sources:
      SRA: "${SRABAM}/{srr}.bam"
      FQ: "${SRAFQ}/{srr}.fastq.gz"
      FQ1: "${SRAFQ}/{srr}_1.fastq.gz"
      FQ2: "${SRAFQ}/{srr}_2.fastq.gz"
  imply:
    - if:
        organism: "Mus musculus"
      then:
        genome: mm10
    - if:
        organism: "Homo sapiens"
      then:
        genome: hg38
    - if:
        read_type: "PAIRED"
      then:
        read1: FQ1
        read2: FQ2
    - if:
        read_type: "SINGLE"
      then:
        read1: FQ1

project_modifiers:
  amend:
    sra_convert:
      looper:
        results_subdir: sra_convert_results
      sample_modifiers:
        append:
          SRR_files: SRA
          pipeline_interfaces: ${CODE}/geofetch/pipeline_interface_convert.yaml
        derive:
          attributes: [read1, read2, SRR_files]
          sources:
            SRA: "${SRARAW}/{srr}/{srr}.sra"
            FQ: "${SRAFQ}/{srr}.fastq.gz"
            FQ1: "${SRAFQ}/{srr}_1.fastq.gz"
            FQ2: "${SRAFQ}/{srr}_2.fastq.gz"





To run pipeline, you should set up few enviromental variables: 1) SRARAW - folder where SRA files were downloaded 2) SRAFQ -folder where fastq should be produced 3) CODE - (first you should clone geofetch), and $CODE is where geofetch folder is located

# Set SRARAW env
export SRARAW=`pwd`
# Create folder where you want to store fq
mkdir fq_folder
# Set SRAFQ env
export SRAFQ=`pwd`/fq_folder
# Unfortunately you have to pull gefetch folder from github, and set CODE variable:
mkdir code && cd code && git clone https://github.com/pepkit/geofetch.git && export CODE=`pwd` && cd ..
ls
build                        processed-data-downloading.ipynb  SRR1930183
code                         python-usage.ipynb                SRR1930184
fq_folder                    raw-data-downloading.ipynb        SRR1930185
how_to_fastq_from_sra.ipynb  red_algae                         SRR1930186

Now install looper if you don't have it

looper --version
looper 1.4.3


ls red_algae
GSE67303_PEP

looper run red_algae/GSE67303_PEP/GSE67303_PEP.yaml -a sra_convert -p local --output-dir .
Looper version: 1.4.3
Command: run
Using default config. No config found in env var: ['DIVCFG']
Using amendments: sra_convert
Activating compute package 'local'
Pipestat compatible: False
## [1 of 4] sample: cm_bluelight_rep1; pipeline: sra_convert
Writing script to /home/bnt4me/virginia/repos/geofetch/docs_jupyter/submission/sra_convert_cm_bluelight_rep1.sub
Job script (n=1; 0.06Gb): ./submission/sra_convert_cm_bluelight_rep1.sub
Compute node: bnt4me-Precision-5560
Start time: 2023-08-01 13:06:42
Using outfolder: ./sra_convert_results/SRR1930183
### Pipeline run code and environment:

*              Command:  `/home/bnt4me/virginia/venv/jupyter/bin/sraconvert --srr /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930183/SRR1930183.sra -O ./sra_convert_results`
*         Compute host:  bnt4me-Precision-5560
*          Working dir:  /home/bnt4me/virginia/repos/geofetch/docs_jupyter
*            Outfolder:  ./sra_convert_results/SRR1930183/
*  Pipeline started at:   (08-01 13:06:42) elapsed: 0.0 _TIME_

### Version log:

*       Python version:  3.10.6
*          Pypiper dir:  `/home/bnt4me/virginia/venv/jupyter/lib/python3.10/site-packages/pypiper`
*      Pypiper version:  0.12.3
*         Pipeline dir:  `/home/bnt4me/virginia/venv/jupyter/bin`
*     Pipeline version:  None

### Arguments passed to pipeline:

*          `bamfolder`:  ``
*        `config_file`:  `sraconvert.yaml`
*             `format`:  `fastq`
*           `fqfolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder`
*           `keep_sra`:  `False`
*             `logdev`:  `False`
*               `mode`:  `convert`
*      `output_parent`:  `./sra_convert_results`
*            `recover`:  `False`
*        `sample_name`:  `None`
*             `silent`:  `False`
*          `srafolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter`
*                `srr`:  `['/home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930183/SRR1930183.sra']`
*          `verbosity`:  `None`

----------------------------------------

Processing 1 of 1 files: SRR1930183
Target to produce: `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder/SRR1930183_1.fastq.gz`  

> `fasterq-dump /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930183/SRR1930183.sra -O /home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder` (744928)
<pre>
spots read      : 1,068,319
reads read      : 2,136,638
reads written   : 2,136,638
</pre>
Command completed. Elapsed time: 0:00:02. Running peak memory: 0.08GB.  
  PID: 744928;  Command: fasterq-dump;  Return code: 0; Memory used: 0.08GB

Already completed files: []

### Pipeline completed. Epilogue
*        Elapsed time (this run):  0:00:02
*  Total elapsed time (all runs):  0:00:02
*         Peak memory (this run):  0.0803 GB
*        Pipeline completed time: 2023-08-01 13:06:44
## [2 of 4] sample: cm_bluelight_rep2; pipeline: sra_convert
Writing script to /home/bnt4me/virginia/repos/geofetch/docs_jupyter/submission/sra_convert_cm_bluelight_rep2.sub
Job script (n=1; 0.04Gb): ./submission/sra_convert_cm_bluelight_rep2.sub
Compute node: bnt4me-Precision-5560
Start time: 2023-08-01 13:06:44
Using outfolder: ./sra_convert_results/SRR1930184
### Pipeline run code and environment:

*              Command:  `/home/bnt4me/virginia/venv/jupyter/bin/sraconvert --srr /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930184/SRR1930184.sra -O ./sra_convert_results`
*         Compute host:  bnt4me-Precision-5560
*          Working dir:  /home/bnt4me/virginia/repos/geofetch/docs_jupyter
*            Outfolder:  ./sra_convert_results/SRR1930184/
*  Pipeline started at:   (08-01 13:06:45) elapsed: 0.0 _TIME_

### Version log:

*       Python version:  3.10.6
*          Pypiper dir:  `/home/bnt4me/virginia/venv/jupyter/lib/python3.10/site-packages/pypiper`
*      Pypiper version:  0.12.3
*         Pipeline dir:  `/home/bnt4me/virginia/venv/jupyter/bin`
*     Pipeline version:  None

### Arguments passed to pipeline:

*          `bamfolder`:  ``
*        `config_file`:  `sraconvert.yaml`
*             `format`:  `fastq`
*           `fqfolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder`
*           `keep_sra`:  `False`
*             `logdev`:  `False`
*               `mode`:  `convert`
*      `output_parent`:  `./sra_convert_results`
*            `recover`:  `False`
*        `sample_name`:  `None`
*             `silent`:  `False`
*          `srafolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter`
*                `srr`:  `['/home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930184/SRR1930184.sra']`
*          `verbosity`:  `None`

----------------------------------------

Processing 1 of 1 files: SRR1930184
Target to produce: `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder/SRR1930184_1.fastq.gz`  

> `fasterq-dump /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930184/SRR1930184.sra -O /home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder` (744973)
<pre>
spots read      : 762,229
reads read      : 1,524,458
reads written   : 1,524,458
</pre>
Command completed. Elapsed time: 0:00:02. Running peak memory: 0.012GB.  
  PID: 744973;  Command: fasterq-dump;  Return code: 0; Memory used: 0.012GB

Already completed files: []

### Pipeline completed. Epilogue
*        Elapsed time (this run):  0:00:02
*  Total elapsed time (all runs):  0:00:02
*         Peak memory (this run):  0.0118 GB
*        Pipeline completed time: 2023-08-01 13:06:47
## [3 of 4] sample: cm_darkness_rep1; pipeline: sra_convert
Writing script to /home/bnt4me/virginia/repos/geofetch/docs_jupyter/submission/sra_convert_cm_darkness_rep1.sub
Job script (n=1; 0.09Gb): ./submission/sra_convert_cm_darkness_rep1.sub
Compute node: bnt4me-Precision-5560
Start time: 2023-08-01 13:06:47
Using outfolder: ./sra_convert_results/SRR1930185
### Pipeline run code and environment:

*              Command:  `/home/bnt4me/virginia/venv/jupyter/bin/sraconvert --srr /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930185/SRR1930185.sra -O ./sra_convert_results`
*         Compute host:  bnt4me-Precision-5560
*          Working dir:  /home/bnt4me/virginia/repos/geofetch/docs_jupyter
*            Outfolder:  ./sra_convert_results/SRR1930185/
*  Pipeline started at:   (08-01 13:06:47) elapsed: 0.0 _TIME_

### Version log:

*       Python version:  3.10.6
*          Pypiper dir:  `/home/bnt4me/virginia/venv/jupyter/lib/python3.10/site-packages/pypiper`
*      Pypiper version:  0.12.3
*         Pipeline dir:  `/home/bnt4me/virginia/venv/jupyter/bin`
*     Pipeline version:  None

### Arguments passed to pipeline:

*          `bamfolder`:  ``
*        `config_file`:  `sraconvert.yaml`
*             `format`:  `fastq`
*           `fqfolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder`
*           `keep_sra`:  `False`
*             `logdev`:  `False`
*               `mode`:  `convert`
*      `output_parent`:  `./sra_convert_results`
*            `recover`:  `False`
*        `sample_name`:  `None`
*             `silent`:  `False`
*          `srafolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter`
*                `srr`:  `['/home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930185/SRR1930185.sra']`
*          `verbosity`:  `None`

----------------------------------------

Processing 1 of 1 files: SRR1930185
Target to produce: `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder/SRR1930185_1.fastq.gz`  

> `fasterq-dump /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930185/SRR1930185.sra -O /home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder` (745021)
<pre>
spots read      : 1,707,508
reads read      : 3,415,016
reads written   : 3,415,016
</pre>
Command completed. Elapsed time: 0:00:03. Running peak memory: 0.079GB.  
  PID: 745021;  Command: fasterq-dump;  Return code: 0; Memory used: 0.079GB

Already completed files: []

### Pipeline completed. Epilogue
*        Elapsed time (this run):  0:00:03
*  Total elapsed time (all runs):  0:00:03
*         Peak memory (this run):  0.0793 GB
*        Pipeline completed time: 2023-08-01 13:06:50
## [4 of 4] sample: cm_darkness_rep2; pipeline: sra_convert
Writing script to /home/bnt4me/virginia/repos/geofetch/docs_jupyter/submission/sra_convert_cm_darkness_rep2.sub
Job script (n=1; 0.07Gb): ./submission/sra_convert_cm_darkness_rep2.sub
Compute node: bnt4me-Precision-5560
Start time: 2023-08-01 13:06:50
Using outfolder: ./sra_convert_results/SRR1930186
### Pipeline run code and environment:

*              Command:  `/home/bnt4me/virginia/venv/jupyter/bin/sraconvert --srr /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930186/SRR1930186.sra -O ./sra_convert_results`
*         Compute host:  bnt4me-Precision-5560
*          Working dir:  /home/bnt4me/virginia/repos/geofetch/docs_jupyter
*            Outfolder:  ./sra_convert_results/SRR1930186/
*  Pipeline started at:   (08-01 13:06:51) elapsed: 0.0 _TIME_

### Version log:

*       Python version:  3.10.6
*          Pypiper dir:  `/home/bnt4me/virginia/venv/jupyter/lib/python3.10/site-packages/pypiper`
*      Pypiper version:  0.12.3
*         Pipeline dir:  `/home/bnt4me/virginia/venv/jupyter/bin`
*     Pipeline version:  None

### Arguments passed to pipeline:

*          `bamfolder`:  ``
*        `config_file`:  `sraconvert.yaml`
*             `format`:  `fastq`
*           `fqfolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder`
*           `keep_sra`:  `False`
*             `logdev`:  `False`
*               `mode`:  `convert`
*      `output_parent`:  `./sra_convert_results`
*            `recover`:  `False`
*        `sample_name`:  `None`
*             `silent`:  `False`
*          `srafolder`:  `/home/bnt4me/virginia/repos/geofetch/docs_jupyter`
*                `srr`:  `['/home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930186/SRR1930186.sra']`
*          `verbosity`:  `None`

----------------------------------------

Processing 1 of 1 files: SRR1930186
Target to produce: `/home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder/SRR1930186_1.fastq.gz`  

> `fasterq-dump /home/bnt4me/virginia/repos/geofetch/docs_jupyter/SRR1930186/SRR1930186.sra -O /home/bnt4me/virginia/repos/geofetch/docs_jupyter/fq_folder` (745069)
<pre>
spots read      : 1,224,029
reads read      : 2,448,058
reads written   : 2,448,058
</pre>
Command completed. Elapsed time: 0:00:02. Running peak memory: 0.081GB.  
  PID: 745069;  Command: fasterq-dump;  Return code: 0; Memory used: 0.081GB

Already completed files: []

### Pipeline completed. Epilogue
*        Elapsed time (this run):  0:00:02
*  Total elapsed time (all runs):  0:00:02
*         Peak memory (this run):  0.0813 GB
*        Pipeline completed time: 2023-08-01 13:06:53

Looper finished
Samples valid for job generation: 4 of 4
Commands submitted: 4 of 4
Jobs submitted: 4


Check if everything worked:

cd fq_folder
ls
SRR1930183_1.fastq  SRR1930184_1.fastq  SRR1930185_1.fastq  SRR1930186_1.fastq
SRR1930183_2.fastq  SRR1930184_2.fastq  SRR1930185_2.fastq  SRR1930186_2.fastq