DeSP: a systematic error Simulation Platform for DNA data storage channel

Getting started with the web app

Live Demo

For a live demo, http://170.106.110.86/ (Silicon Valley, US)

In case that the web app doesn't response, you can also:

Run the web app locally

Clone or download this repository, and install the dependencies:

git clone https://github.com/WangLabTHU/DeSP

# install packages
# under python 3.x
pip install matplotlib numpy plotly seaborn streamlit scipy reedsolo prettytable

Navigate to the project folder, and run the app:

# move to the project folder
cd download/DeSP main

streamlit run main.py

Navigate to localhost:8501. You should see the app running in your broswer :)

Embed the channel model in your research pipeline

You can construct a model, use the model to generate simulated sequencing readouts, and analysis the sequencing reults following the scripts below:

from Model.Model import *
import Model.config as config

# editting parameters of the channel
arg = config.DEFAULT_PASSER
arg.seq_depth = 10

# construct a channel by linking modules
Modules = [
  ('synthesizing',Synthesizer(arg)),
  ('decaying',Decayer(arg)),
  ('pcring',PCRer(arg = arg)),
  ('sampling',Sampler(arg = arg)),
  ('sequencing',Sequencer(arg))
]
Model = DNA_Channel_Model(Modules)

# load the data, and use the model to generate simulated sequencing results
with open('files/lena.dna') as f:
dnas = f.readlines()
in_dnas = [dna.split('\n')[0] for dna in dnas]
out_dnas = Model(in_dnas)

# examine the output dnas
from Analysis.Analysis import inspect_distribution, examine_strand
inspect_distribution(out_dnas, show = True) # oligo number and error number distribution of the entire sequencing results
examine_strand(out_dnas, index = index) # sequencing readouts and voting result of a single sequence.

Jupyter notebooks and experiment data

Notebooks

Notebooks to reproduce figures in the paper are also provided.

• Analysis of Individual Stages of DNA data channel.ipynb (Corresponding to part 2.1 of the paper)
• Validation.ipynb (Correspond to part 3.1 of the paper)
• Step-by-step simulation.ipynb (Part 3.2 of the paper)
• Encoding Design.ipynb (Part 3.3 of the paper)

To use the notebooks, please download the project and install the dependencie following the instructions above first.

Data

The experimental sequencing data used in the paper are provided in seq_data.csv and seq_data.pkl. Data in the two files are the same, the pickle file is just for fast loading in python scripts. Please download the data from https://cloud.tsinghua.edu.cn/d/157100ca4c8e4fd387e1/, and move the data to files/ before running the validation notebook.

Acknowledgements

Code about the DNA Fountain code is adopted from https://github.com/TeamErlich/dna-fountain.