Tutorial

This tutorial describes the use of IMDA using the provided test data set in the Download section. In addition, this IMDAtest data contains the barcode.txt file required for MIGEC processing.

Please go sure you followed the instructions in Download and install all required Third party software tools. Further, follow all instructions for the Path settings.

Step 1: Open the settings.py with your Python 3 environment (e.g., IDLE, PyCharm, VS, Spyder,…) or with a text editor (e.g., Editor, Notepad++, WordPad,…)

Step 2: Adapt all paths to the third party software tools as described in the Path settings. Paths to the files in the provided test dataset (IMDAtest) look as follows:

### Path to Folder (defines input and output folder) ###
global_path="**PATH_TO_TESTDATA**/IMDAtest/"

### Path to Folder with Files ###
in_path= glob_path + "Input/FASTQ/"
undetermined_path = glob_path + "Input/Undetermined/"

### Path to Barcode File (barcodes.txt) and FACS Correction File (pairs) ###
barcode_file = glob_path + "Input/barcodes.txt"
facs_correction_file = glob_path + "Input/pairs.txt"

Step 3: Give your IMDAtest run a title

### Run Informations ###
RUN = "IMDA Test Data"

Step 4: IMDA test data derive from apparently healthy individuals (humans) and the target sequence was the T cell receptor \({\beta}\) chain (TRB). Specify your T or B cell properties as follows:

### B or T cell chain ###
chain = "TRB"
species = "hsa"

Step 5: Now, we want to specify the analyses we want to perform. We only have to change the lines from do_Bowtie. If we don’t have performed do_MIGEC and do_MiXCR before, set the methods as follows:

do_Bowtie=True,
do_MIGEC=True,
do_MiXCR=True,
do_VDJtools=True,
do_FACSCorrection=False,
do_ContaminationProcessing=False,
do_ContaminationAnalysis=False,
do_EvaluateUndetermined=True,
do_ClonalityAnalysis=True,
do_DiversityAnalysis=True,
do_OverlapAnalysis=False,
do_SimilarityAnalysis=True,
do_VDJAnalysis=False

This means that…

  • we are pre-processing our NGS data (do_MIGEC, do_MiXCR and do_VDJtools),
  • we want to analyze the undetermined reads (do_Bowtie) and evaluate them (do_EvaluateUndetermined),
  • and we perform clonality (do_ClonalityAnalysis), diversity (do_DiversityAnalysis) and similarity (do_SimilarityAnalysis) analysis.

Step 5: Finally, we want to start the IMDA pipeline.

  • Python environment: If you use a Python 3 environment (e.g., IDLE, PyCharm, VS, Spyder,…) run the settings.py code.

  • Text editor: If you opened the settings.py with your text editor, please save (and close) this file. Open your terminal or command line and follow the next steps:

    • Windows: enter cmd in the path section of the IMDA folder or Start > cmd.exe > cd PATH_TO_IMDA**/IMDA/
    • Linux: open the terminal and navigate to IMDA: cd PATH_TO_IMDA**/IMDA/
    • enter the following command: python settings.py or python3 settings.py