Merge pull request #141 from nasa/DEV_Methylseq_250115

Update Methyl Seq pipeline as follows:

Added a filtering and normalization step prior to differential methylation analysis. For studies in which the coverage is fairly similar across the samples, this step will not change the results, but in the case of outliers it will improve the data quality. See Step 11e for the complete implementation details, in brief:

Normalize the data

First, filter samples by coverage to account for PCR bias or over-amplification
meth_obj <- filterByCoverage(meth_obj, lo.count = 10, lo.perc = NULL, hi.count = NULL, hi.perc = 99.9)

Normalize coverage between samples using a scaling factor derived from the median coverage distributions
norm_meth_obj <- normalizeCoverage(meth_obj, method = "median")

Combined all pair-wise differential methylation analyses into one output table for bases and one output table for tiles, rather than providing individual sets of files for each comparison and splitting between hypo and hyper methylated regions.

Provided the differential methylation output without filtering, rather than imposing significance cutoffs.

The new output format matches the output formats we provide for our other assay types.

Author: asaravia-butler

Methyl-Seq/Pipeline_GL-DPPD-7113_Versions/GL-DPPD-7113.md

@@ -0,0 +1,9 @@
+from pathlib import Path
+
+# Import for access at the module level
+from . import checks
+from . import protocol
+from . import schemas
+
+# Set config path
+config = Path(__file__).parent / "methylSeqDNA_v2.yaml"