Sample re-identification pipeline:

This pipeline enables the usage of the minION generated DNA reads for re-identification of DNA samples.

Cell line authentication:

Re-identification of cell lines in (pre-) clinical research is crucial to verify working materials. Using the MinION in conjunction with our identification pipeline allows sample authentication on-site: either in the lab or in the clinic.

Requirements for running the pipeline are a cell line database and minION reads.

Database:

The database for Cancer Cell line authentication is available at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE36139 .

The Cancer Cell line database is built from data generated by the CCLE (Broad Institute: https://portals.broadinstitute.org/ccle/).

MinION reads:

The MinION libraries can be prepared by the appropriate genomics library preparation method provided by Oxford Nanopore Technologies. Input material ranges from 200ng-1000ng. https://nanoporetech.com/

Re-identification of forensic samples:

Database:

The database for forensic purposes is not provided here to respect genetic privacy of the individuals in our database.

Publically available genomes: OpenSNP: https://opensnp.org/genotypes

MinION reads:

The MinION libraries can be prepared by the appropriate genomics library preparation method provided by Oxford Nanopore Technologies.

Analysis pipeline

Prerequisites

The pipeline requires the following components:

• wget, GNU sed, and other standard unix command-line programs
• samtools, bgzip, tabix http://www.htslib.org/
• BWA https://github.com/lh3/bwa
• Python 2.7 with following python modules:
  • poretools https://github.com/arq5x/poretools
  • numpy, scipy
  • pysam
• For plotting - R <www.r-project.org> with these libraries:
  • hexbin
  • RColorBrewer
  • gplots
  • naturalsort
  • optparse

Detailed Installation Instructions

These programs have been tested on Ubuntu 14.04 64bit GNU/Linux machine. Other environments might require some adjustments.

Download the latest pipeline code

# Using GIT
git clone https://github.com/TeamErlich/personal-identification-pipeline
cd personal-identification-pipeline

# Or using ZIP
wget https://github.com/TeamErlich/personal-identification-pipeline/archive/master.zip
unzip master.zip

The setup directory contains helper script to install the required software:

# Install required packages:
sudo ./setup/setup-ubuntu1404.sh

# Install python modules:
sudo pip install -r ./setup/requirements.txt

# Install samtools 1.3.1 (will use 'sudo' automatically)
./setup/setup-samtools.sh

# Install bgzip/tabix 1.3.1 (will use 'sudo' automatically)
./setup/setup-htslib.sh

# Install BWA 0.7.15 (will use 'sudo; automatically)
./setup/setup-bwa.sh

Building data files

The personal-identification pipeline requires few pre-processed data files.

Download hg19 reference genome, build BWA index (this will take some time, depending on the machine's hardware. About ~70m on a 2.5Ghz Intel XEON E5):

./setup/setup-hg19.sh

Download dbSNP-138 Common and build db (requires downloading ~620MB, will take some time depending on the network speed):

./setup/setup-snp138common.sh

Optionally, download Yaniv Erlich's genotype file:

./setup/setup-YE-genotype.sh

Example

The demo directory contains a simplified example of the pipeline workflow. See ./demo/README.md for more details.

Test re-ID:

DIR THP1 FAST5 files: https://s3.amazonaws.com/archive-store7/thp1-minion-files.tar.gz

THP1 SNP-array-file: https://github.com/TeamErlich/personal-identification-pipeline/tree/master/data

Example usage for THP1 re-id:

./run-personal-id-pipeline.sh test-run THP1-FAST5-dir/ thp1-snp-file-dir/ hg19/hg19.fa

-or-

./run-personal-id-pipeline.sh –s snp138Common.fixed.txt.gz test-run THP1-FAST5-dir/ thp1-snp-file-dir/ hg19/hg19.fa

Help and Usage information

The following scripts support help and usage information with the --help parameter (-h in case of the shell script):

run-personal-id-pipeline.sh -h
poretools-basenames.py --help
sam-to-bedseq.py --help
sam-discard-dups.py --help
generate-snp-list.py --help
calc-match-probs.py --help
calc-match-probs-parallel.sh --help
filter-high-prob-matches.sh --help

“Rapid DNA Re-Identification for Cell Line Authentication and Forensics” Zaaijer et al., 2017

Contact

Yaniv Erlich [email protected] Sophie Zaaijer [email protected]

http://TeamErlich.org

License

Copyright (C) 2016 Yaniv Erlich ([email protected])

All Rights Reserved. This program is licensed under GPL version 3. See LICENSE file for full details.