MinVar is a command-line tool to discover mutations conferring drug resistance in HIV-1 and HCV populations using deep sequencing data.

[user@host ~]$ minvar -f sample_file.fastq
... a few minutes later ...
[user@host ~]$ column -t -s ',' merged_muts_drm_annotated.csv
gene      pos  mut  freq    category
...
RT        238  T    1.0     NNRTI
RT        250  N    0.9547  unannotated
RT        272  P    1.0     unannotated
RT        293  V    1.0     unannotated
RT        297  A    1.0     unannotated
RT        333  D    0.9384  unannotated
RT        333  E    0.0354  unannotated
RT        335  C    1.0     unannotated
protease  10   P    0.0223  Other
protease  10   Q    0.0185  Other
protease  10   S    0.0741  Other
protease  10   T    0.0468  Other
protease  10   V    0.5948  PIMinor
protease  11   L    1.0     PIMinor
protease  13   V    1.0     unannotated
protease  14   R    1.0     unannotated
protease  15   V    0.7143  unannotated
protease  20   T    1.0     PIMinor
protease  32   I    1.0     PIMajor
...

• MinVar is an opinionated software: it just takes a fastq file as input and does not ask the standard user to set any parameter at run time. Nevertheless, the experienced user/developer can easily change some of its settings in the source code.
• It has been tested with HIV-1 on both Illumina MiSeq and Roche/454 sequencing reads. HCV has been tested on MiSeq only.
• It uses state-of-the-art third tools to filter, recalibrate, and align reads and to call variants.
• Finally, single nucleotide variants are phased at codon level and amino acid mutations are called and annotated.
• HIV-1 drug-resistance mutations are annotated according to Stanford HIV Drug Resistance Database (HIVDB).
• The annotated mutations are saved in a csv file (see example above) and also included in a report in markdown format that is finally converted to PDF.
• The PDF report can be customized by adding contact information specified in the file ~/.minvar/contact.ini with the following syntax (only change what comes after the = sign)

[contact]
unit = name_of_your_unit_here
phone = phone_number
fax = fax_number
email = your_unit@your_company
logo = filename_without_extension

The logo file in pdf format must be present in the same directory. In other words, if we want to use the file ~/.minvar/company_logo_bw.pdf, then in the INI file we will write logo = company_logo_bw.

See the official documentation.

API documentation can be created by cloning this repo, cd-ing into apidoc and running make html.

MinVar (version 1, HIV-1 support only) has been introduced and validated in
Huber, Metzner et al., (2017) MinVar: A rapid and versatile tool for HIV-1 drug resistance genotyping by deep sequencing Journal of virological methods 240:7-13, doi:10.1016/j.jviromet.2016.11.008

• subtype_evidence.csv percent of reads best aligned to each subtype (or genotype),
• subtype_ref.fasta references of the subtype identified,
• cns_final.fasta: sample consensus created by iteratively aligning reads and writing variants into the sequence,

• hq_2_cns_final_recal.bam sorted bam alignment of reads to the consensus sequence, recalibrated with either GATK or lofreq (indels only),
• hq_2_cns_final_recal.vcf VCF file of mutations found on reads with respect to consensus in cns_final.fasta.

• merged_mutations_nt.csv a list of all variants observed at single positions,
• max_freq_muts_aa.csv the amminoacid found at maximum frequency at each codon,
• final.csv mutations at amminoacid level with indication of the gene, the position on the gene, wild type and frequency

• merged_muts_drm_annotated.csv is the join of final.csv with the annotation of DRM/RAS,
• report.md and report.pdf final report with subtye estimate based on alignment of reads to different references and tables with mutations. The pdf report is created from the template minvar/db/template.tex.