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specify counts columns in manual_drops #46

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Apr 24, 2024
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specify counts columns in manual_drops #46

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0e817e3
specify counts columns to use for manual_drops with "wells" or "barc…
ckikawa Apr 23, 2024
914c5bd
update CHANGELOG with changes in v3.1.1
ckikawa Apr 23, 2024
bdda519
update CHANGELOG with linked issue
ckikawa Apr 23, 2024
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3 changes: 3 additions & 0 deletions CHANGELOG.md
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@@ -1,5 +1,8 @@
# CHANGELOG

#### version 3.1.1
- Minor bug fix to make it possible to add `wells` or `barcodes` to the `manual_drops` specified for each plate. Addresses [this issue](https://github.com/jbloomlab/neutcurve/issues/45).

### version 3.1.0
- Configured to enable plate-level indices to be embedded in the round-1 PCR primers (see [this issue](https://github.com/jbloomlab/seqneut-pipeline/issues/40)). Essentially, this amounts to allowing a per-plate flanking sequence to be specified for each plate, and only FASTQ reads with that flanking sequence are read for that plate. Typically this index would be specified as `upstream2` in the [illuminabarcodeparser](https://jbloomlab.github.io/dms_variants/dms_variants.illuminabarcodeparser.html). To enable this change, altered the configuration from the previous setup of just having a single global `illumina_barcode_parser_params` applied to all plates. Now such a global parser is still specified that has default values that you want to apply to all plates. But in addition, in the per-plate configuration you can specify `illumina_barcode_parser_params` that are added to (and override) anything in the global parser params, and can contain plate specific `upstream2` and other relevant setting (eg, `upstream2_mismatch`). The test example was modified to use this option for plate2 and plate11.

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6 changes: 5 additions & 1 deletion notebooks/process_plate.py.ipynb
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Expand Up @@ -296,6 +296,10 @@
" )\n",
" )[\"barcode_serum_replicate\"].isin(qc_drops[filter_type])\n",
" ]\n",
" elif filter_type == \"wells\":\n",
" counts = counts[~counts[\"well\"].isin(qc_drops[filter_type])]\n",
" elif filter_type == \"barcodes\":\n",
" counts = counts[~counts[\"barcode\"].isin(qc_drops[filter_type])]\n",
" else:\n",
" assert filter_type in set(counts.columns)\n",
" counts = counts[~counts[filter_type].isin(qc_drops[filter_type])]"
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.2"
"version": "3.11.7"
}
},
"nbformat": 4,
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