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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.

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  • $\begingroup$ The metrics from FastQC are more of a snapshot. It depends on your sequencing platform used. Was it illumina, iontorrent, pacbio? $\endgroup$
    – AudileF
    Jul 14, 2017 at 11:25
  • $\begingroup$ The sequencing platform is illumina. Primarily miseq. I just don't want to regret not recording information that might be useful later. $\endgroup$
    – Dan K
    Jul 14, 2017 at 11:56
  • $\begingroup$ Well all the important info for illumina will be stored in basespace you would be looking at cluster density and the Q-score. $\endgroup$
    – AudileF
    Jul 14, 2017 at 11:58
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    $\begingroup$ Is there any reason not to keep all of it? $\endgroup$
    – terdon ♦
    Jul 14, 2017 at 12:22
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    $\begingroup$ 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. $\endgroup$
    – Bioathlete
    Jul 15, 2017 at 17:54

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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

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