Pipeline Project

This is a python-based pipeline that is structured to compare HCMV transcriptomes 2 and 6 days post infection (dpi) and assemble the genome based on the given transcriptomes.

Getting Started

• To clone this directory, run the following on the command line:

  git clone https://github.com/gchilton1102/Pipeline_Project_Grace_Chilton.git

• If you do not already have Python installed, follow the instructions on this page: https://www.python.org/downloads/

You will need the following dependencies:

• The following libraries are part of the standard library of python version 2.7 or later:

  argparse

  sys

  os

  subprocess

  glob

• Separate installations, run the following on the command line:

  pip install biopython

Retrieve transcriptomes from patients infected with HCMV 2 and 6 days post infection from SRA

• Run the following commands to download the transcriptome SRA files from each Donor to your machine/server:

  Donor 1 (2dpi): wget https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR5660030/SRR5660030

  Donor 1 (6dpi): wget https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR5660033/SRR5660033

  Donor 3 (2dpi): wget https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR5660044/SRR5660044

  Donor 3 (6dpi): wget https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR5660045/SRR5660045

• Run the following commands to uncompress the retrieved data:

  fastq-dump -I --split_files SRR5660030

  fastq-dump -I --split_files SRR5660033

  fastq-dump -I --split_files SRR566004

  fastq-dump -I --split_files SRR5660045

• Move all fastq files to the Pipeline_Project_Grace_Chilton directory, created with the git clone command

Running the wrapper script

• Run the following on the command line:

  python3 wrapper.py -i name_of_transcriptome_folder/

• Substitue "name_of_transcriptome_folder" with the full filepath to the transcriptome fastq files downloaded in the previous step

• Make sure your fastq files are within the Pipeline_Project_Grace_Chilton directory

Testing Pipeline with Sample Data

Sample data for this pipeline is included in the sample_data directory included in this GitHub repository

When testing with the sample data, include the sample data after the -i flag

The following is the command to run with the sample data on the command line, make sure you are working in the Pipeline_Project_Grace_Chilton directory:

python3 wrapper.py -i sample_data/