10 Matching Annotations
  1. Last 7 days
    1. 160 samples

      If we won’t know whether 1 sample = 1 donation I would call that out explicitly.

    2. SARS

      Looks like we only got SARS reads in two samples. This is a good candidate for validating with BLAST if there's time.

    3. species

      Also noteworthy that we saw a lot of anelloviridae in the Cebria Mendoza RNA MGS paper.

      Maybe we have both RNA and DNA stages of anelloviridae get picked up, or maybe the RNA > cDNA sample prep just also got a bunch of anelloviridae DNA in it.

    4. e preparation/library preparation is not taken

      I would highlight/link the Cebria Mendoza paper here.

    5. Popular/Well-known Name

      This is a great addition. I think it would actually be better to use the popular names in the above RA plot as well.

      We may also have some data source internally at SB that has a mapping from NCBI taxonomic virus name to common name.

    6. exclude Anelloviridae

      Why exclude Anelloviridae?

      I think it would make sense to have a version of this plot with human reads removed as we discussed in the context of Cebria Mendoza paper.

    7. 2.2 Quality control metrics

      Can the two QC sections be combined or are they stage specific?

    8. 3.2 Total viral content

      I would make this a histogram. You can make two histograms - one for classified reads and one for all reads.

    9. 4.1 Overall relative abundance

      I still think making a histogram is the way to go for this plot

    10. p_reads_max

      What is p_reads_max?