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bcbio priorities #3242

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1 of 90 tasks
naumenko-sa opened this issue May 27, 2020 · 2 comments
Open
1 of 90 tasks

bcbio priorities #3242

naumenko-sa opened this issue May 27, 2020 · 2 comments
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@naumenko-sa
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naumenko-sa commented May 27, 2020

Long TODO lists don't get done.
We are trying to keep an issue open if a real effort is happening to resolve it.
The below priority list gives a sense of where bcbio is heading in the next two releases.

Issues from the lower circles are re-opened and pushed to circle one,
when there is bandwidth to work on them.

Contributions are welcome to rescue an issue from any circle!

Closed issues and implemented features are described in the release notes.

Priority circle 1 ~ ~ release 1.3.0 ~ Q2 2022

  • update transcriptome gtf from ensembl 94 to ensembl 104 - TSL1-3

Priority circle 2

Priority circle 3

new functionality

Priority circle 4

Technical debt

The issues below don't break production, however, it is good to have them solved at some point.
Contributions welcome - pick an issue, ask to re-open the issue if you are working on it.
Some of them are good for the first contribution to bcbio.

Reference issues

Closed issues where no work is needed but which contain some valuable information (validations, great expertise and discussion). for better visibility.

@naumenko-sa naumenko-sa pinned this issue May 27, 2020
@naumenko-sa naumenko-sa self-assigned this May 27, 2020
@roryk roryk self-assigned this May 27, 2020
@roryk roryk changed the title pinned bcbio priorities bcbio priorities May 27, 2020
@roryk
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roryk commented May 29, 2020

If anyone wants to tag in and work on any of this stuff, we are happy to help orient.

@lbeltrame
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cfDNA calling: test and integrate ichor

I can help with this, as I've used the package extensively (200+ samples so far). It would probably need some tweaking for low fraction samples.

On cfDNA front it might be worth investigating in silico size selection, which in my tests improves sensitivity a lot. The rationale is explained in https://pubmed.ncbi.nlm.nih.gov/30404863/, which describes a dual approach (both during library preparation and during analysis), but in my experience just filtering BAMs by query size length helps. I have proof-of concept code that does this step, which we use internally.

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