Genomic amplification of oncogenes and inactivation of suppressor genes are critical in the pathogenesis of human cancer. To identify chromosomal alterations associated with hepatocarcinogenesis, we performed allelic gene dosage analysis on 36 hepatocellular carcinomas (HCCs). Data from high-density single-nucleotide polymorphism arrays were analysed using the Genome Imbalance Map (GIM) algorithm, which simultaneously detects DNA copy number alterations and loss of heterozygosity (LOH) events. Genome Imbalance Map analysis identified allelic imbalance regions, including uniparental disomy, and predicted the coexistence of a heterozygous population of cancer cells. We observed that gains of 1q, 5p, 5q, 6p, 7q, 8q, 17q and 20q, and LOH of 1p, 4q, 6q, 8p, 10q, 13q, 16p, 16q and 17p were significantly associated with HCC. On 6q24-25, which contains imprinting gene clusters, we observed reduced levels of PLAGL1 expression owing to loss of the unmethylated allele. Finally, we integrated the copy number data with gene expression intensity, and found that genome dosage is correlated with alteration in gene expression. These observations indicated that high-resolution GIM analysis can accurately determine the localizations of genomic regions with allelic imbalance, and when integrated with epigenetic information, a mechanistic basis for inactivation of a tumor suppressor gene in HCC was elucidated.