Metadata-Version: 2.1
Name: PeptidesSearch
Version: 0.2.1
Summary: Search a list of peptides in a fasta file (or proteome) and returns exact matches or hits with one mismatch
Home-page: https://github.com/khaledianehdieh/PeptidesSearch
Author: Ehdieh Khaledian
Author-email: khaledianehdieh@gmail.com
License: MIT
Download-URL: https://pypi.org/project/PeptidesSearch/
Keywords: Peptide Search,Peptide Match,One Mismatch,Exact Match,python,Peptide,Protein
Platform: UNKNOWN
Description-Content-Type: text/markdown

A useful tools to search a list of peptides in a fasta file (a list of proteins, or a proteome)

# Description
    
This tool consists one module:

- `PeptideSearch`: this tool searches for peptides in a fasta file including proteins, it can find Exact Match or Marches with up to One Mismatch 

# Installation
 
## Normal installation

```bash
pip install PeptideSearch
```

## Development installation

```bash
git clone https://github.com/khaledianehdieh/PeptideSearch.git
```

## Usage

```
python3
>>> from PeptideSearch import PeptideSearch as PS 
>>> P=PS.PeptideSearch(Peptides, Fasta_File) #Peptides is a .txt file that has one peptide per line, and Fasta_File is a fasta file containing the proteins

#you might use the function as you need in three different ways:
#1- Find Exact Matches
>>> df_EM, pList= P.ExactMatch()  # returns Exact Matches (df_EM) and a list of peptides (pList) that didn't find any matche

#2- Find One MisMatches
>>> peptides= P.read_Peptides()
df_OM, NotFoundList= P.OneMismatch(peptides) #returns One  Mis Matches (df_OM) for and list of peptides (NotFoundList) that didn't find any matche

#3- Combine one and two, first find a list of exacxt matches and then look for one mismatch for the peptides that we diddnt find any match
#Also saves the result in a CSV file
>>> df_all, NotFounPeptides = P.MatchFinder()   #returns All Matches (df_all) for and a list of peptides (NotFounPeptides) that couldn't find any match

```


# Change log

## [0.1] - 2021-08-02
- Created

## [0.2.1] - 2021-08-02
- Added usage


