diff --git a/CHANGELOG.md b/CHANGELOG.md index c105566..e1d4e49 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -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. diff --git a/notebooks/process_plate.py.ipynb b/notebooks/process_plate.py.ipynb index fff8ebc..3216f83 100644 --- a/notebooks/process_plate.py.ipynb +++ b/notebooks/process_plate.py.ipynb @@ -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])]" @@ -1501,7 +1505,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.2" + "version": "3.11.7" } }, "nbformat": 4,