Hepatitis C virus (HCV) is classified into seven major genotypes and 67 subtypes. Recent studies have shown that in HCV genotype 1-infected patients, response rates to regimens containing direct-acting antivirals (DAAs) are subtype dependent. Currently available genotyping methods have limited subtyping accuracy. We have evaluated the performance of a deep-sequencing-based HCV subtyping assay, developed for the 454/GS-Junior platform, in comparison with those of two commercial assays (Versant HCV genotype 2.0 and Abbott Real-time HCV Genotype II) and using direct NS5B sequencing as a gold standard (direct sequencing), in 114 clinical specimens previously tested by first-generation hybridization assay (82 genotype 1 and 32 with uninterpretable results). Phylogenetic analysis of deep-sequencing reads matched subtype 1 calling by population Sanger sequencing (69% 1b, 31% 1a) in 81 specimens and identified a mixed-subtype infection (1b/3a/1a) in one sample. Similarly, among the 32 previously indeterminate specimens, identical genotype and subtype results were obtained by direct and deep sequencing in all but four samples with dual infection. In contrast, both Versant HCV Genotype 2.0 and Abbott Real-time HCV Genotype II failed subtype 1 calling in 13 (16%) samples each and were unable to identify the HCV genotype and/or subtype in more than half of the non-genotype 1 samples. We concluded that deep sequencing is more efficient for HCV subtyping than currently available methods and allows qualitative identification of mixed infections and may be more helpful with respect to informing treatment strategies with new DAA-containing regimens across all HCV subtypes. ; Journal Article; Research Support, Non-U.S. Gov't; Corrección: Volume 53, no. 1, p. 219–226, 2015. Page 221, Table 1: The sequence for primer 13N5Bo8254 should read “GTTGTAAAACGACGGCCAGTCNTAYGAYACCMGNTGYTTTGACTC.” ; This study has been supported by CDTI (Centro para el Desarrollo Tecnológico Industrial), Spanish Ministry of Economics and Competitiveness (MINECO), IDI-20110115; MINECO projects SAF 2009-10403; and also by the Spanish Ministry of Health, Instituto de Salud Carlos III (FIS) projects PI10/01505, PI12/01893, and PI13/00456. CIBERehd is funded by the Instituto de Salud Carlos III, Madrid, Spain. Work at CBMSO was supported by grant MINECO-BFU2011-23604, FIPSE and Fundación Ramón Areces.