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. 2012 May;54(1):30-5.
doi: 10.1016/j.jcv.2012.01.018. Epub 2012 Mar 16.

Automated sequence analysis and editing software for HIV drug resistance testing

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Automated sequence analysis and editing software for HIV drug resistance testing

Daniel Struck et al. J Clin Virol. 2012 May.

Abstract

Background: Access to antiretroviral treatment in resource-limited-settings is inevitably paralleled by the emergence of HIV drug resistance. Monitoring treatment efficacy and HIV drugs resistance testing are therefore of increasing importance in resource-limited settings. Yet low-cost technologies and procedures suited to the particular context and constraints of such settings are still lacking. The ART-A (Affordable Resistance Testing for Africa) consortium brought together public and private partners to address this issue.

Objectives: To develop an automated sequence analysis and editing software to support high throughput automated sequencing.

Study design: The ART-A Software was designed to automatically process and edit ABI chromatograms or FASTA files from HIV-1 isolates.

Results: The ART-A Software performs the basecalling, assigns quality values, aligns query sequences against a set reference, infers a consensus sequence, identifies the HIV type and subtype, translates the nucleotide sequence to amino acids and reports insertions/deletions, premature stop codons, ambiguities and mixed calls. The results can be automatically exported to Excel to identify mutations. Automated analysis was compared to manual analysis using a panel of 1624 PR-RT sequences generated in 3 different laboratories. Discrepancies between manual and automated sequence analysis were 0.69% at the nucleotide level and 0.57% at the amino acid level (668,047 AA analyzed), and discordances at major resistance mutations were recorded in 62 cases (4.83% of differences, 0.04% of all AA) for PR and 171 (6.18% of differences, 0.03% of all AA) cases for RT.

Conclusions: The ART-A Software is a time-sparing tool for pre-analyzing HIV and viral quasispecies sequences in high throughput laboratories and highlighting positions requiring attention.

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