This repository contains the data processing and analysis pipeline for random access of DNA-archived data using Cas9 enrichment and nanopore sequencing.
Our data processing pipeline uses an adapted version of the C3POa software package associated with the publication https://www.pnas.org/doi/10.1073/pnas.1806447115. This is found in the software directory.
In software/blat, a stand-alone version of the BLAT software from https://genome.ucsc.edu/cgi-bin/hgBlat is included. BLAT is called by C3POa to perform alignment.
This code was developed and tested on Jupyter using Python 3.7.
The following packages should be installed separately:
- numpy (1.16.2)
- matplotlib (2.2.4)
- poa (1.0.0 revision: 1.2.2.9)
- gonk
- minimap (2 2.7-r654)
- racon
Clone this repository and install the required dependencies.
In software/config.txt, specify the absolute path to the executables listed in the file.
In the second cell of the 20200715_triple_file_access.ipynb notebook, replace [PATH] with the absolute path to this cloned repository.
The directory 20200715_basecalled_reads contains FASTQ files of nanopore reads that passed basecalling. These reads came from an experiment where 3 files (file #2, #13, and #24) were accessed from a pool of 25 files.
An example analysis of these reads is presented in the notebook 20200715_triple_file_access.ipynb. In the Preprocessing and Processing sections of this notebook, the reads are demultiplexed into their respective files and a consensus sequence is called for each concatemeric read using C3POa. These consensus sequences are stored in FASTA format in 20200715_results/consensus. The Analysis section of this notebook uses these consensus reads to generate relevant figures.