README.md

QASeq

Description

QASeq (quantitative amplicon sequencing) is a PCR-based molecular barcoding NGS workflow, published as an article on Nature Communications. This code base provides a bioinformatics pipeline for analyzing sequencing data generated with QASeq, with formatted tables and figures as outputs. Scheme of QASeq workflow

Install (Linux x64 or Mac Intel chip)

1. Install Miniconda if not installed already (quick command line install)

2. Create a new Conda environment named "qaseq" and install packages needed

conda create -n QASeq pysam bowtie2 biopython matplotlib-base seaborn pandas scipy xlrd xlwt openpyxl pytables tqdm jupyterlab --channel conda-forge --channel bioconda --channel defaults --strict-channel-priority

3. Activate the environment

conda activate QASeq

4. Clone this repository and install QASeq

git clone https://github.com/mxwang66/QASeq.git
cd QASeq
python -m pip install . --no-deps --no-build-isolation --no-cache-dir

Dependencies

python >=3.8
pysam
bowtie2
biopython
numpy
pandas
seaborn
matplotlib
scipy
xlrd
xlwt
openpyxl
pytables
jupyterlab
tqdm

Usage

Input files

• Design spreadsheet (example: Olivar-multi preliminary design 102723-2 formated.xlsx).

• .fastq.gz outputs from sequencer (paired-end, Illumina sequencer).

1. Create an empty folder for the NGS run

e.g., a directory named 20240830_test_run

2. Make a copy of run-analysis.ipynb inside the run folder

3. Place all .fasta.gz files in the raw_reads folder, under the run folder

e.g., 20240830_test_run/raw_reads

4. Activate Conda environment and start JupyterLab

conda activate qaseq
jupyter lab

5. Navigate to the run folder, open run-analysis.ipynb and follow the instructions

Input your library names and path to the design spreadsheet, as well as other parameters.