Methylize

- Minor edits to readme and removing methylcheck import, because it is not used anywhere.
- Note: methylprep is only imported for reading Manifest files and handling ArrayType.

- We found that `diff_meth_pos` results were not accurate in prior versions and have fixed the regression optimization.
- `diff_meth_pos` function kwargs changed to provide more flexibility in how the model is optimized.
- Added support for COVARIATES in logistic regression. Provide a dataframe with both the phenotype and covariates, and specify which columns are phenotype or covariates. It will rearrange and normalize to ensure the model works best.
- Use the new 'solver' kwarg in `diff_meth_pos` to specify which form of linear or logistic regression to run. There are two flavors of each, and both give nearly identical results.
- Auto-detects logistic or linear based on input: if non-numeric inputs in phenotype of exactly two values, it assumes logistic.
- Upgraded manhattan and volcano plots with many more options. Default settings should mirror most R EWAS packages now, with a "suggestive" and "significant" threshold line on manhattan plots.
- Unit test coverage added.

- Fixed option to use Differentially methylated regions (DMR) via cached local copy of UCSC database (via fetch_genes) without using the internet. Previously, it would still contact the internet database even if user told it not to.
- Added testing via github actions, and increased speed
- updated documentation

- fixed bug in fetch_genes() from UCSC browser; function will now accept either the filepath or the DMR dataframe output.

- Added a differentially methylated regions (DMR) functions that takes the output of the `diff_meth_pos` (DMP) function.
- DMP maps differences to chromosomes; DMR maps differences to specific genomic locii, and requires more processing.
- upgraded methylprep manifests to support both `old` and `new` genomic build mappings for all array types.
In general, you can supply a keyword argument (`genome_build='OLD'`) to change from the new build back to the old one.
- Illumina 27k arrays are still not supported, but mouse, epic, epic+, and 450k ARE supported.
(Genome annotation won't work with `mouse` array, only human builds.)
- DMP integrates the `combined-pvalues` package (https://pubmed.ncbi.nlm.nih.gov/22954632/)
- DMP integrates with UCSC Genome (refGene) and annotates the genes near CpG regions.
- Annotation includes column(s) showing the tissue specific expression levels of relevant genes (e.g. `filter=blood`)
this function is also available with extended options as `methylize.filter_genes()`
- provides output BED and CSV files for each export into other genomic analysis tools
- `methylize.to_BED` will convert the diff_meth_pos() stats output into a standard BED file
(a tab separated CSV format with standardized, ordered column names)

- fixed methylize diff_meth_pos linear regression. upgraded features too
- Fixed bug in diff_meth_pos using linear regression - was not calculating p-values correctly.
Switched from statsmodels OLS to scipy linregress to fix, but you can use either one with kwargs.
They appear to give exactly the same results now after testing.
- The "CHR-" prefix is omitted from manhattan plots by default now
- dotted manhattan sig line is Bonferoni corrected (pass in post_test=None to leave uncorrected)
- added a probe_corr_plot() undocumented function, a scatterplot of probe confidence intervals vs pvalue
- sorts probes by MAPINFO (chromosome location) instead of FDR_QValue on manhattan plots now
- Support for including/excluding sex chromosomes from DMP (probe2chr map)