Detect HIV Drug Resitant Mutations using amplicon sequencing data
A production-ready re-implementation of https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699007/, https://github.com/Wei-Shao/HIV-DRLink.
- Install conda (if not already present): https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.html
- Install mamba:
conda install mamba -n base -c conda-forge - Clone hivdrm:
git clone https://github.com/bcbio/hivdrm.git cd hivdrm- Create conda environment to run hivdrm:
mamba env create -n hivdrm_production --file environment.yml - add hivdrm to PATH:
export PATH=/path/to/hivdrm:$PATHin .bashrc or .bash_profile
conda activate hivdrm_production
cd /path/project
hivdrm.py \
--barcodes barcodes.csv \
--reference reference.edited.fasta \
--threads 10 \
r1.fq.gz r2.fq.gz
conda deactivateSome clusters/batch systems require source activate/deactivate instead of conda activate/deactivate.
Example of barcodes.csv:
Sample_ID,Primers,F-Linkers,R-Linkers
S01,F1/R1,CGCCTG,GCCATG
S02,F1/R2,CGCCTG,TACAAG
S03,F1/R3,CGCCTG,ATTCCG
S04,F1/R4,CGCCTG,TCGGGA
S05,F1/R5,CGCCTG,GAATGA
S06,F1/R6,CGCCTG,GCCTAA
S07,F2/R1,CGTGAT,GCCATG
S08,F2/R2,CGTGAT,TACAAG
S09,F2/R3,CGTGAT,ATTCCG
S10,F2/R4,CGTGAT,TCGGGA
S11,F2/R5,CGTGAT,GAATGA
S12,F2/R6,CGTGAT,GCCTAA
S13,F3/R1,CTGATC,GCCATG
Example of reference.fasta:
>EF602219.1 HIV-1 isolate 1779 from South Africa pol protein (pol) gene, partial cds edited
CGCCTGAATCCATATAACACTCCAATATTTGCCATAAAAAAGAAGGACAGTACTAAGTGGAGAAAATTAGTAGATTTCAGGGAACTTAATAAAAGAACTCAAGACTTTTGGGAAGTTCAATTAGGAATACCACATCCAGCAGGATTAAAAAAGAAAAAATCAGTGACAGTACTGGATGTGGGGGATGCATATTTTTCAGTTCCTTTAGATGAAGGCTTCAGAAAATATACTGCATTCACCATACCTAGTATAAACAATGAAACACCAGGGATTAGATATCAATATAATGTGCTCCCAGGATCACCAGCAATATTCCAAAGTAGCATGACAAAAATCTTAGAGCCCTTTAGAGCAAGAAATCCAGAAATAGTCATCTATCAATATATGGATGACTTGTATGTGGGATCTGACTTAGAAATAGGGCAACATAGAGCAAAAATAGAGGAATTAAGAGCACATTTATTAGGGTGGGGATTTACCACWCCAGACAAGAAACATCAGAAGGAACCCCCATTTCTTTGGATGGGGTACGAACTCCATCCTGACAAATGGACAGTNNNNNNNNNNCTAGCAGGATGACTTCGATACCCATGGC
Barcode processing steps for libraries with multiple samples and blastn step benefit a lot from multithreading. Consider running on a server/cluster with 10 threads/20G RAM.
- DRM.xlsx - 1st sheet - DRM stats, then one sheet per sample
- freq.xlsx - barcode stats, per sample all and top allele frequencies
_hivdrm_tmp- intermediate files from all the steps
conda remove --name hivdrm_production --all
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