<p>I would say that the following metrics are useful:</p>

<ul>
<li>Sample source (Extraction place, person, date)</li>
<li>Details about pre-HTS preparation (e.g. amplicon PCR, rRNA removal)</li>
<li>Reads per sample (+ per barcode / lane, if available)</li>
<li>Sequencing kit (e.g. TruSeq v3), useful for adapter trimming</li>
<li>Sequence length (e.g. 125bp)</li>
<li>Paired end / single end</li>
<li>If paired end, target fragment length in sample prep (e.g. 650bp)</li>
<li>Reference sequence metadata

<ul>
<li>Scientific name</li>
<li>Location of reference genome (preferably a stable web address)</li>
<li>Version of reference genome</li>
<li>Read mapping rate (per sample / barcode / lane), as a percentage of total reads</li>
<li>Mapping program + version</li>
</ul></li>
<li>If available, potential contaminating organisms

<ul>
<li>Name / description</li>
<li>Location of contaminant sequence (preferably a stable web address)</li>
<li>Estimated mapping rate (bearing in mind that there may be some overlap with the target)</li>
<li>Mapping program + version</li>
</ul></li>
</ul>

<p>More generally, ENA / EBI has an excellent reference in sample checklists, which indicate the minimum acceptable metadata for attaching to sequence archive data:</p>

<p><a href="https://www.ebi.ac.uk/ena/submit/checklists" rel="nofollow noreferrer">https://www.ebi.ac.uk/ena/submit/checklists</a></p>

CC BY-SA 3.0
2017-10-15T11:43:28.523Z
2018-01-28T22:09:15.393Z
2018-01-28T22:09:15.393Z
gringer
<p>I'm new to bioinformatics and Im starting a new microbial sequencing project and I'd like to record all of the qc data correctly. This is research and I'm not sure what I'll need later. Is there any consensus on useful qc metrics to record in a database for each sequencing run?</p>

<p>No rnaseq, running FastQC, assembling with a defined reference for a single species. </p>

CC BY-SA 3.0
2017-07-14T11:25:46.370Z
The metrics from FastQC are more of a snapshot. It depends on your sequencing platform used. Was it illumina, iontorrent, pacbio?
AudileF
CC BY-SA 3.0
2017-07-14T11:56:50.443Z
The sequencing platform is illumina. Primarily miseq. I just don't want to regret not recording information that might be useful later.
Dan K
CC BY-SA 3.0
2017-07-14T11:58:25.187Z
Well all the important info for illumina will be stored in basespace you would be looking at cluster density and the Q-score.
AudileF
CC BY-SA 3.0
2017-07-14T12:22:08.427Z
Is there any reason not to keep all of it?
terdon
CC BY-SA 3.0
2017-07-14T12:23:37.377Z
No, just wanted to distill the essentials into a local database if possible.
Dan K
CC BY-SA 3.0
2017-07-14T14:23:19.807Z
What it might not be essential today might be essential in a couple of years. You can always delete it later, but you can't recover data after years of the experiment
llrs
CC BY-SA 3.0
2017-07-15T17:54:52.620Z
If you are using a MiSeq is your data stored on basespace or locally?  If it is on basespace then the QC metrics should be store there for you.  If locally then you can go into the run data and pull the metrics files from the Illumina reports.  Really you are looking for information about clustering etc.  The sequencing quality and read metrics can be recalculated from the fastq/Bam files at any time.
Bioathlete
CC BY-SA 3.0
2017-07-15T18:07:27.497Z
@AaronBerlin we're storing locally. Thanks for the suggestions.
Dan K
CC BY-SA 3.0
2017-07-16T13:07:26.427Z
This also depends what you want to do with the data. The FASTQs already have all the quality scores stored, so it's easy to re-create all the QC outputs if necessary. MultiQC is good at making these reports: http://multiqc.info/

If you're planning to assemble them, the metrics matter a bit more. You'd want to record things like coverage depth, number of contigs, length of contigs etc. People usually report N50 for example
Joe Healey
<database><ngs><qc>
What sequencing data metrics should I record?
# What sequencing data metrics should I record?

(Asked by: username_0 on 2017-07-14)

I'm new to bioinformatics and Im starting a new microbial sequencing project and I'd like to record all of the qc data correctly. This is research and I'm not sure what I'll need later. Is there any consensus on useful qc metrics to record in a database for each sequencing run?

No rnaseq, running FastQC, assembling with a defined reference for a single species.

**Tags:** database, ngs, qc
> **Comments:**
> **username_1**: The metrics from FastQC are more of a snapshot. It depends on your sequencing platform used. Was it illumina, iontorrent, pacbio?  
> **username_0**: The sequencing platform is illumina. Primarily miseq. I just don't want to regret not recording information that might be useful later.  
> **username_1**: Well all the important info for illumina will be stored in basespace you would be looking at cluster density and the Q-score.  
> **username_2**: Is there any reason not to keep all of it?  
> **username_0**: No, just wanted to distill the essentials into a local database if possible.  
> **username_3**: What it might not be essential today might be essential in a couple of years. You can always delete it later, but you can't recover data after years of the experiment  
> **username_4**: If you are using a MiSeq is your data stored on basespace or locally?  If it is on basespace then the QC metrics should be store there for you.  If locally then you can go into the run data and pull the metrics files from the Illumina reports.  Really you are looking for information about clustering etc.  The sequencing quality and read metrics can be recalculated from the fastq/Bam files at any time.  
> **username_0**: @AaronBerlin we're storing locally. Thanks for the suggestions.  
> **username_5**: This also depends what you want to do with the data. The FASTQs already have all the quality scores stored, so it's easy to re-create all the QC outputs if necessary. MultiQC is good at making these reports: http://multiqc.info/  If you're planning to assemble them, the metrics matter a bit more. You'd want to record things like coverage depth, number of contigs, length of contigs etc. People usually report N50 for example  

---

## 1 answers

### Answer by username_6 on 2017-10-15. Score: 3

I would say that the following metrics are useful:

* Sample source (Extraction place, person, date)
* Details about pre-HTS preparation (e.g. amplicon PCR, rRNA removal)
* Reads per sample (+ per barcode / lane, if available)
* Sequencing kit (e.g. TruSeq v3), useful for adapter trimming
* Sequence length (e.g. 125bp)
* Paired end / single end
* If paired end, target fragment length in sample prep (e.g. 650bp)
* Reference sequence metadata
  + Scientific name
  + Location of reference genome (preferably a stable web address)
  + Version of reference genome
  + Read mapping rate (per sample / barcode / lane), as a percentage of total reads
  + Mapping program + version
* If available, potential contaminating organisms
  + Name / description
  + Location of contaminant sequence (preferably a stable web address)
  + Estimated mapping rate (bearing in mind that there may be some overlap with the target)
  + Mapping program + version

More generally, ENA / EBI has an excellent reference in sample checklists, which indicate the minimum acceptable metadata for attaching to sequence archive data:

<https://www.ebi.ac.uk/ena/submit/checklists>


---

