new workflow to deal with multiple basecalls from same flowcell #325
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| Map[String, String] ref_map = read_map(ref_map_file) | ||
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| String outdir = sub(gcs_out_root_dir, "/$", "") + "/ONTFlowcell/~{flowcell}" |
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Are you sure output is meant to go into the usual ONTFlowcell directory? I'm fine with that, but just wanted to check that this is what you intended.
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yes, that's intended. the multiple basecalls themselves are output to a different dir
long-read-pipelines/wdl/ONTBasecall.wdl
Line 15 in a7527a5
It's done this way so that flowcell level data are all stored in ONTFlowcell.
One disparity between 1-basecall flowcells and 1+-basecall flowcells is that the latter has many metrics stored in the basecalls directory, and how they should be aggregated to the flowcell level is to be done in the planned overhaul.
Thoughts?
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| version 1.0 | ||
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| import "../../../tasks/Utility/Utils.wdl" as Utils | ||
| import "../../../tasks/Utility/GeneralUtils.wdl" as GU |
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What are Utils vs GeneralUtils?
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| Map[String, Float] raw_reads_stats = nanoplot_map | ||
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| Map[String, Float] aligned_reads_stats = NanoPlotFromBam.stats_map |
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This is fine for now, but at some point I really would like us to rethink a few things. This output is not particularly conducive to easy analysis in Jupyter notebooks. The answer could be to have some official boilerplate code that presents the Terra table as a pandas dataframe or an R tibble, with the maps here exploded out as columns.
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Yep. The little library that I'm going to present on tomorrow can support this easily.
…directories * one workflow that essentially copies current ONTFlowcell, but aims at a basecall directory * one workflow that plays the role of ONTFlowcell, but actually aggregates results from the WF above
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