I'm hoping some experts who know the ins-and-outs of using NCBI better than I do can help me with this fairly basic question.
I'm looking at a specific BioProject (Accession PRJDB11398). The abstract says it contains samples from 3 different patient groups: those with periodontitis, those with gingivitis, and healthy people. However, I cannot find any metadataabout the runs. Am I missing the secret data source that would allow me to know which of these 252 BioSamples correspond to which disease group?
Second, related question: I can find no publication associated with this data. Am I not looking in the right place? Are there some "tricks" to finding a publication that perhaps did not get linked to its associated BioProject? This data was collected at Tokyo Medical and Dental University; is it possible that there is a non-English publication somewhere that is not indexed in Pubmed and, if so, any tips on how I might find it?
EDIT: found the paper via a Google search. So, yes Google search is the trick to finding a paper associated with a BioProject and no, they are not always properly linked.
Thanks in advance.
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sovrappensiero •
You can query SRA by using EntrezDirect to get information about the runs. Here is an example snippet.
$ esearch -db sra -query "PRJDB11398" | efetch -format runinfo
Run,ReleaseDate,LoadDate,spots,bases,spots_with_mates,avgLength,size_MB,AssemblyName,download_path,Experiment,LibraryName,LibraryStrategy,LibrarySelection,LibrarySource,LibraryLayout,InsertSize,InsertDev,Platform,Model,SRAStudy,BioProject,Study_Pubmed_id,ProjectID,Sample,BioSample,SampleType,TaxID,ScientificName,SampleName,g1k_pop_code,source,g1k_analysis_group,Subject_ID,Sex,Disease,Tumor,Affection_Status,Analyte_Type,Histological_Type,Body_Site,CenterName,Submission,dbgap_study_accession,Consent,RunHash,ReadHash
DRR280789,2021-08-24 14:16:09,2021-08-24 14:21:18,76047,19783022,0,260,8,,https://sra-download.ncbi.nlm.nih.gov/traces/dra2/DRR/000274/DRR280789,DRX270372,,RNA-Seq,cDNA,METATRANSCRIPTOMIC,SINGLE,0,0,ILLUMINA,Illumina MiSeq,DRP007622,PRJDB11398,,757640,DRS202294,SAMD00288208,simple,447426,human oral metagenome,SAMD00288208,,,,,,,no,,,,,TOKYO_MEDEN,DRA011737,,public,CC21F307E5AB3AD9A5FC8C111E35DECB,32894C9FA91BD1719B942C8905CDD991
DRR280790,2021-08-24 14:16:09,2021-08-24 14:51:38,14603,3729248,0,255,1,,https://sra-download.ncbi.nlm.nih.gov/traces/dra2/DRR/000274/DRR280790,DRX270373,,RNA-Seq,cDNA,METATRANSCRIPTOMIC,SINGLE,0,0,ILLUMINA,Illumina MiSeq,DRP007622,PRJDB11398,,757640,DRS202295,SAMD00288209,simple,447426,human oral metagenome,SAMD00288209,,,,,,,no,,,,,TOKYO_MEDEN,DRA011737,,public,8448A0733DDE58ACE33791803DDC0B7B,BD15A6A02DF59D32588860D35EBDDD07
It is possible that there is no publication associated with the data yet. Since I don't see anything when querying PubMed with this accession. This is probably not fool-proof.
You can also use NCBI SRA Run selector to see some information. Click on the Metadata link to download a slightly different table than one above.
Run,Assay Type,AvgSpotLen,Bases,BioProject,BioSample,Bytes,Center Name,Consent,DATASTORE filetype,DATASTORE provider,DATASTORE region,Experiment,Instrument,Library Name,LibraryLayout,LibrarySelection,LibrarySource,Organism,Platform,ReleaseDate,Sample Name,sample_name,SRA Study
DRR280689,RNA-Seq,260,30555000,PRJDB11398,SAMD00288108,15437534,TOKYO_MEDEN,public,sra,"gs,ncbi,s3","gs.US,ncbi.public,s3.us-east-1",DRX270272,Illumina MiSeq,,SINGLE,cDNA,METATRANSCRIPTOMIC,human oral metagenome,ILLUMINA,2021-08-24T00:00:00Z,SAMD00288108,sample10G_afterdec_Fp_clean.fq,DRP007622
DRR280690,RNA-Seq,246,8921381,PRJDB11398,SAMD00288109,5551730,TOKYO_MEDEN,public,sra,"gs,ncbi,s3","gs.US,ncbi.public,s3.us-east-1",DRX270273,Illumina MiSeq,,SINGLE,cDNA,METATRANSCRIPTOMIC,human oral metagenome,ILLUMINA,2021-08-24T00:00:00Z,SAMD00288109,sample10G_afterdec_Fup_clean.fq,DRP007622
DRR280691,RNA-Seq,165,19393221,PRJDB11398,SAMD00288110,12754105,TOKYO_MEDEN,public,sra,"gs,ncbi,s3","gs.US,ncbi.public,s3.us-east-1",DRX270274,Illumina MiSeq,,SINGLE,cDNA,METATRANSCRIPTOMIC,human oral metagenome,ILLUMINA,2021-08-24T00:00:00Z,SAMD00288110,sample10G_afterdec_Rp_clean.fq,DRP007622
Thanks, GenoMax! I found this Metadata link...I don't see information about the patient's status/disease group. I think this must mean they didn't upload it. I just wanted to be sure I wasn't missing something obvious.
I figured it out! The samples have labels like 10G, 10P, 10H, which corresponds to the different disease states (G, P, H) in a single patient's mouth (patient number 10). Each set of forward and reverse reads have different IDs (e.g. for patient 10: DRR280689 and DRR280691 are the F and R reads, and DRR280690 is unpaired reads...). A little bit odd.
Thank you, again!
great, thanks for sharing what you found,
and I can't help but shake my head when I learn, that even though there are myriad metadata fields, the most important information that identifies that sample origin had to be guessed and parsed out from inside a name.
Also found the paper via Google search. So, to answer my own question, yes the linking between Pubmed ID and BioProject is a bit...flimsy.
allow me to plug my cool package bio a bit (https://www.bioinfo.help/) that you could use like so:
bio search PRJDB11398
prints JSON like this:
[
{
"run_accession": "DRR280940",
"sample_accession": "SAMD00288359",
"first_public": "2021-08-29",
"country": "",
"sample_alias": "SAMD00288359",
"fastq_bytes": "87567",
"read_count": "731",
"library_name": "",
"library_strategy": "RNA-Seq",
"library_source": "METATRANSCRIPTOMIC",
"library_layout": "SINGLE",
"instrument_platform": "ILLUMINA",
"instrument_model": "Illumina MiSeq",
"study_title": "Comparison of microbiome of periodontitis, gingivitis, and healthy",
"fastq_ftp": "ftp.sra.ebi.ac.uk/vol1/fastq/DRR280/DRR280940/DRR280940.fastq.gz"
}
...
]
you can process the json with tools like jq or ask for the output as comma-separated fields like so:
bio search PRJDB11398 --csv
to get:
DRR280939,SAMD00288358,2021-08-29,,SAMD00288358,33669337,288229,,RNA-Seq,METATRANSCRIPTOMIC,SINGLE,ILLUMINA,Illumina MiSeq,"Comparison of microbiome of periodontitis, gingivitis, and healthy",ftp.sra.ebi.ac.uk/vol1/fastq/DRR280/DRR280939/DRR280939.fastq.gz
DRR280940,SAMD00288359,2021-08-29,,SAMD00288359,87567,731,,RNA-Seq,METATRANSCRIPTOMIC,SINGLE,ILLUMINA,Illumina MiSeq,"Comparison of microbiome of periodontitis, gingivitis, and healthy",ftp.sra.ebi.ac.uk/vol1/fastq/DRR280/DRR280940/DRR280940.fastq.gz
now the above selects the most commonly used fields, to actually get all the metadata
bio search PRJDB11398 --all
it prints things like:
{
"accession": "SAMD00288359",
"altitude": "",
"assembly_quality": "",
"assembly_software": "",
"base_count": "105313",
"binning_software": "",
"bio_material": "",
"broker_name": "",
"cell_line": "",
"cell_type": "",
"center_name": "TOKYO_MEDEN",
"checklist": "",
"collected_by": "",
"collection_date": "",
"collection_date_submitted": "",
"completeness_score": "",
"contamination_score": "",
"country": "",
"cram_index_aspera": "",
"cram_index_ftp": "",
"cram_index_galaxy": "",
"cultivar": "",
"culture_collection": "",
"depth": "",
"description": "Illumina MiSeq sequencing; Illumina MiSeq sequencing of SAMD00288359",
"dev_stage": "",
"ecotype": "",
"elevation": "",
"environment_biome": "",
"environment_feature": "",
"environment_material": "",
"environmental_package": "",
"environmental_sample": "false",
"experiment_accession": "DRX270523",
"experiment_alias": "DRX270523",
"experiment_title": "Illumina MiSeq sequencing; Illumina MiSeq sequencing of SAMD00288359",
"experimental_factor": "",
"fastq_aspera": "fasp.sra.ebi.ac.uk:/vol1/fastq/DRR280/DRR280940/DRR280940.fastq.gz",
"fastq_bytes": "87567",
"fastq_ftp": "ftp.sra.ebi.ac.uk/vol1/fastq/DRR280/DRR280940/DRR280940.fastq.gz",
"fastq_galaxy": "ftp.sra.ebi.ac.uk/vol1/fastq/DRR280/DRR280940/DRR280940.fastq.gz",
"fastq_md5": "6547d173a825a3da2ee89df2b0fa045f",
"first_created": "2021-08-29",
"first_public": "2021-08-29",
"germline": "false",
"host": "Homo sapiens",
"host_body_site": "",
"host_genotype": "",
"host_gravidity": "",
"host_growth_conditions": "",
"host_phenotype": "",
"host_sex": "",
"host_status": "",
"host_tax_id": "9606",
"identified_by": "",
"instrument_model": "Illumina MiSeq",
"instrument_platform": "ILLUMINA",
"investigation_type": "",
"isolate": "",
"isolation_source": "",
"last_updated": "2021-08-29",
"lat": "",
"library_construction_protocol": "",
"library_layout": "SINGLE",
"library_name": "",
"library_selection": "cDNA",
"library_source": "METATRANSCRIPTOMIC",
"library_strategy": "RNA-Seq",
"location": "",
"lon": "",
"mating_type": "",
"nominal_length": "",
"nominal_sdev": "",
"parent_study": "",
"ph": "",
"project_name": "",
"protocol_label": "",
"read_count": "731",
"run_accession": "DRR280940",
"run_alias": "DRR280940",
"salinity": "",
"sample_accession": "SAMD00288359",
"sample_alias": "SAMD00288359",
"sample_capture_status": "",
"sample_collection": "",
"sample_description": "sample9P_afterdec_Rup_clean.fq",
"sample_material": "",
"sample_title": "sample9P_afterdec_Rup_clean.fq",
"sampling_campaign": "",
"sampling_platform": "",
"sampling_site": "",
"scientific_name": "human oral metagenome",
"secondary_sample_accession": "DRS202445",
"secondary_study_accession": "DRP007622",
"sequencing_method": "",
"serotype": "",
"serovar": "",
"sex": "",
"specimen_voucher": "",
"sra_aspera": "fasp.sra.ebi.ac.uk:/vol1/drr/DRR280/DRR280940",
"sra_bytes": "158541",
"sra_ftp": "ftp.sra.ebi.ac.uk/vol1/drr/DRR280/DRR280940",
"sra_galaxy": "ftp.sra.ebi.ac.uk/vol1/drr/DRR280/DRR280940",
"sra_md5": "02d7286bc443f8aff5418ca1144dd624",
"strain": "",
"study_accession": "PRJDB11398",
"study_alias": "DRP007622",
"study_title": "Comparison of microbiome of periodontitis, gingivitis, and healthy",
"sub_species": "",
"sub_strain": "",
"submission_accession": "DRA011737",
"submission_tool": "",
"submitted_aspera": "",
"submitted_bytes": "",
"submitted_format": "",
"submitted_ftp": "",
"submitted_galaxy": "",
"submitted_host_sex": "",
"submitted_md5": "",
"submitted_sex": "",
"target_gene": "",
"tax_id": "447426",
"taxonomic_classification": "",
"taxonomic_identity_marker": "",
"temperature": "",
"tissue_lib": "",
"tissue_type": "",
"variety": ""
}
Thanks, Istvan! This is pretty cool. It looks to me like they didn't upload the disease group for each BioSample. This json is quite nice!
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How useful would it be to go from a bioproject accession to a nf-core manifest?
FWIW I have no idea what an nf-core manifest is or what use it has - perhaps that should be the first thing to do, to demonstrate on a larger scale
when you hit that launch green button here it generates a manifest that describes the sample layout for a nf-core run