define "true" viral barcodes

[jbloom]

@dbacsik says:

The main question right now is how we define and filter "true" viral barcodes from the transcriptome data and from the supernatant/second infection sequencing data.

The data show a lot of viral barcodes that are unique to each sequencing sample. The number of unique viral barcodes in the sequencing far exceeds the plausible number of virions infected into the cells (~1.25e4 visions). To distinguish real barcodes from errors, I have used the following filtering criteria:

• The barcode must be present in the “cell” (first infection) sample. It stands to reason that any real barcode present in the supernatant or second infection should be derived from the first infection.
  • The barcode must be present above some threshold frequency.

This works OK, and there are reasonable correlations between the barcodes in the first infection, supernatant, and second infection. However, there is still substantial noise, and the raw data still shows barcodes that are present at high frequency in the supernatant or second infection but not found in the first infection.

[jbloom]

I think UMI_tools has methods for figuring out "true" barcodes from mismatches that could be applied to the viral barcodes within single cells.

Within the whole mix, there is some complicated set of viral barcodes. That is true both if we look at all barcodes over transcriptomics (across cells) or if we look at all barcodes in the supernatant.

We really only care about the viral barcodes that are in the transcriptomics.

Furthermore, within each cell, we expect there to be only at most a few distinct viral barcodes.

My suggestion is that first we identify truly infected cells in the transcriptomics.

Then we use the transcriptomic viral barcode calls to use something like UMI_tools to figure out what are the true viral barcode in that cell. And then we have our set of true viral barcodes in the transcriptomic data.

[jbloom]

If we take this approach, we need to #58

[dbacsik]

A few ideas came out of our discussion about this issue today:

• As you noted above, in a low MOI infection, each cell should only have one or a few distinct viral barcodes. We can use UMI tools to correct all the barcodes within a cell in the transcriptomics data.
• I expect the edit distance between true barcodes to be quite large. We are only sampling a few thousand barcodes from a potential nt space of billions. I will try to plot the edit distance between each pairwise comparison.
• I will examine the progeny viral barcode data to see if barcodes are ever shared between WT and dblSyn variant libraries. The infections and sequencing for the two viral tags are handled totally independently. If they are fully unique, we can use the barcode information to assign tag identities to cells.

[dbacsik]

This nebulous issue has been superseded by more specific tasks. I am closing it.