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How to use AlFinder

##1) Downloading

Instructions

Download ALL documents from https://github.com/tbigot/alFinder and save them in the same folder (e.g. NGS_analysis). To perform this step, you can use git:

git clone https://github.com/tbigot/alFinder.git

or the download link on this repository website.

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├── alFinder.py
├── COPYING
├── data
│   ├── 1.fas
│   ├── 1_result.csv
│   ├── 1_unknownAlleles.csv
│   ├── 2.TCA.454Reads.fna
│   ├── Mama-DRB1.fas
│   ├── Mama-DRB1_new.fas
│   ├── Mama-DRB2.fas
│   ├── Mama-DRB2_new.fas
│   ├── Mama-UB.fas
│   ├── Mama-UB_new.fas
│   ├── Mama-UD.fas
│   ├── Mama-UD_new.fas
│   ├── tags.csv
│   └── tagsRun1.csv
├── example
│   ├── alleles_locus1.fas
│   ├── alleles_locus2.fas
│   ├── alleles_locus3.fas
│   ├── alleles_locus4.fas
│   ├── correspondenceData.csv
│   ├── data.fna
│   ├── output_example
│   │   ├── alleles_locus1.fas_filtered
│   │   ├── alleles_locus2.fas_filtered
│   │   ├── alleles_locus3.fas_filtered
│   │   ├── alleles_locus4.fas_filtered
│   │   ├── data_filteredResults.csv
│   │   └── data_result.csv
│   ├── postprocessing.py
│   ├── README.md
│   ├── settings.ini
│   └── tags.csv
├── individual.py
├── individual.pyc
├── postprocessing.py
├── README.md
├── read.py
├── settings.ini
└── settings.sample.ini

Requirements

Works on any system with python available.

##2) Test the program with the example

First try the demonstration, located in the example folder of the previously created folder (e.g. NGS_analysis)

  1. In the example folder the user can find an example based on the method described in the following article:

Large-scale genotyping by next generation sequencing: how to overcome the challenges to reliably genotype individuals? Ferrandiz-Rovira M, Bigot T, Allainé D, Callait-Cardinal M-P, Cohas A.

  • the file data.fna contains the output data from the sequencing machine
  • the file tags.csv contains the tags
  • the files alleles_locus1.fas, alleles_locus2.fas, alleles_locus3.fas and alleles_locus4.fas contain the previously described alleles for four loci
  • the file correspondenceData.csv contains the correspondence file
  • the output_example folder contains outputs from the example settings
  • the file settings.ini is modified according to the method described in the article and is ready to be use
  • the file postprocessing.py is modified according to the method described in the article and is ready to be use
  1. Copy all the python files (alFinder.py, individual.py, read.py, postprocessing.py) to the example directory
  2. Open the terminal (if python is not installed in your computer please download and install it on https://www.python.org/)
  3. Use the command cd or C: depending on the operating system of your computer (linux/mac and Windows) to go in the directory where ALL downloaded documents have been saved (e.g. cd /home/NGS_analysis/example)
  4. Call alFinder.py file in the terminal (type python alFinder.py in the terminal)
  5. Call postprocessing.py file in the terminal (type python postprocessing.py in the terminal)
  6. Close the terminal
  7. You can find the results in the previously created folder (e.g. NGS_analysis/example)
    • the file data_result.csv is the obtained result after typing python alFinder.py in the terminal
    • the file data_filteredResults.csv is the obtained result after typing python postprocessing.py in the terminal
    • the files intermediateResults are generated after each step (see article)

##3) Use it with your own data You run succesfully the example, now try it on your own data

  1. Put your own data in the previously created folder (e.g. NGS_analysis):
  • a file with the output data from the sequencing machine
  • a file with the tags
  • a file/files with the previously described alleles (if no previously described alleles: an empty file should be present for each locus)
  • if necessary: the correspondence file
  1. Modify settings.ini according to your needs, save and close it (see example in the settings.ini of the example folder)
  2. Modifiy postprocessing.py according to your needs, save and close it (see example in the postprocessing.py of the example folder)
  3. Open the terminal
  4. Use the command cd or C: depending on the operating system of your computer (linux/mac and Windows) to go in the directory where ALL downloaded documents have been saved (e.g. cd /home/NGS_analysis)
  5. Call alFinder.py file in the terminal (type python alFinder.py in the terminal)
  6. Call postprocessing.py file in the terminal (type python postprocessing.py in the terminal)
  7. You can find the results in the previously created folder (e.g. NGS_analysis)

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