semvec/pypi-packages huggingface dataset:
comp-path 0.1.2
A package for analyzing compensated pathogenic deviation
Requires Python: >=3.7

# Compensated Pathogenic Deviations (CPDs)

## Required python packages
- Bio: https://biopython.org/wiki/Download
- BeautifulSoup: https://www.crummy.com/software/BeautifulSoup/bs4/doc/#installing-beautiful-soup
- variation-number: https://github.com/jiaying2508/variation_number

## Required external packages
- emboss needle: https://www.bioinformatics.nl/cgi-bin/emboss/help/needle

## Running instructions for installation using pip
```console
$ pip install comp-path
```

## Usage
```
from comp_path import CpdClass
import os

currDir = os.getcwd()
outputDir = '{}/output'.format(currDir)
gene = 'BRCA1'
uniprot = 'P38398'
cpdModel = CpdClass(gene, uniprot, outputDir)

# get orthologs sequences
acc = cpdModel.getFasta()

# download clinVar records
cpdModel.getClinvarRecords(email='')

totalMutation, totalMutationDict = cpdModel.getPathogenicMutations()
print('total number of pathogenic mutations is: {}'.format(len(totalMutation)))
for key in totalMutationDict:
    print(key, len(totalMutationDict[key]))

# get CPDs
cpdModel.getCPDs(similarity=0.5, gap=10, percent_match=0.4, skipAlignment=False)
totalSpecies = cpdModel.totalSpecies
filteredSpecies = cpdModel.filteredSpecies
homoSeq = cpdModel.homoSeq
print('total orthologs: ', len(totalSpecies),
    ' >50%% similarity sequences: ', len(filteredSpecies))
print('homo sapien {} length: {} aa'.format(gene, len(homoSeq)))

# perform analysis on CPDs
cpdModel.analyzeCPDs()
print('the length of homoSeq {} is {}, the length of featuredRegion is {}, \
    \ntotal unique CPD positions is {}, {} CPDs fall in the featured Region.'
    .format(cpdModel.gene, len(cpdModel.homoSeq), len(cpdModel.featuredRegion), 
    cpdModel.totalCPDPos, cpdModel.featureCPD))
    
# get PDB residue pairs
cpdInPDB = cpdModel.getResiduePairs(dist=8, getPDB=True)
print('Total number of interacting residue pairs is ', cpdModel.numInteracting)
print('PDB structure length is:', len(cpdModel.pdbPosSet))
print('number of CPDs in PDB structure', cpdInPDB)

numComp, compCPD = cpdModel.getCompSites()
print('the number of potential compensatory sites is: ',
    numComp, 'for {} unique CPDs'.format(compCPD))
```
nashidentitysync 0.0.2
Python library for connecting to the Nash Identity Framework

# Nasheq E.R.P. Standardized A.P.I.s python integrations

## Quick Guide
Below are the steps on how to get the web app up and running

1.	Install it:
```bash
    pip install nashkycidentitysync
```
2.	View get started documentation:
```bash
    https://nashbanksuite.readme.io/v1.2.0/docs
```
3.	Start Coding