This study introduces a genome-wide scoring system called the Residual Variation Intolerance Score (RVIS) to assess how well genes tolerate functional genetic variation. The RVIS is derived from sequence data of 6,503 whole exomes from the NHLBI Exome Sequencing Project (ESP). The score measures the deviation from expected common functional variation in genes, based on the amount of neutral variation in the gene. Genes with higher RVIS values are more intolerant to functional variation, indicating a higher likelihood of being involved in disease. The study shows that genes responsible for Mendelian diseases have significantly higher RVIS values than genes not associated with disease. However, there is variation in RVIS among different disease classes. For example, genes linked to developmental disorders are more intolerant to functional variation than those linked to immunological disorders. The RVIS can help prioritize candidate mutations in personal genomes and identify pathogenic mutations. The RVIS is calculated by regressing the number of common functional variants (Y) against the total number of variants (X) in a gene. The residual from this regression is then standardized to account for differences in mutational burden. The RVIS is then converted into a percentile to reflect the relative rank of the gene. The study also explores the relationship between RVIS and other measures of selection, such as the Ka/Ks ratio. It finds that RVIS is not strongly correlated with these measures. The RVIS is shown to be a useful tool for predicting OMIM disease gene lists and for identifying genes that are more likely to cause disease. The study also investigates the relationship between RVIS and the age of onset of diseases. It finds that genes causing early-onset diseases tend to have lower RVIS values than those causing late-onset diseases. This suggests that the RVIS can be used to prioritize genes based on their likelihood of causing disease. The study also explores the use of the RVIS in combination with variant-level scores, such as PolyPhen-2, to prioritize mutations. It finds that combining gene-level and variant-level information improves the ability to identify causal mutations. The RVIS is shown to be a useful tool for interpreting personal genomes and identifying pathogenic mutations.This study introduces a genome-wide scoring system called the Residual Variation Intolerance Score (RVIS) to assess how well genes tolerate functional genetic variation. The RVIS is derived from sequence data of 6,503 whole exomes from the NHLBI Exome Sequencing Project (ESP). The score measures the deviation from expected common functional variation in genes, based on the amount of neutral variation in the gene. Genes with higher RVIS values are more intolerant to functional variation, indicating a higher likelihood of being involved in disease. The study shows that genes responsible for Mendelian diseases have significantly higher RVIS values than genes not associated with disease. However, there is variation in RVIS among different disease classes. For example, genes linked to developmental disorders are more intolerant to functional variation than those linked to immunological disorders. The RVIS can help prioritize candidate mutations in personal genomes and identify pathogenic mutations. The RVIS is calculated by regressing the number of common functional variants (Y) against the total number of variants (X) in a gene. The residual from this regression is then standardized to account for differences in mutational burden. The RVIS is then converted into a percentile to reflect the relative rank of the gene. The study also explores the relationship between RVIS and other measures of selection, such as the Ka/Ks ratio. It finds that RVIS is not strongly correlated with these measures. The RVIS is shown to be a useful tool for predicting OMIM disease gene lists and for identifying genes that are more likely to cause disease. The study also investigates the relationship between RVIS and the age of onset of diseases. It finds that genes causing early-onset diseases tend to have lower RVIS values than those causing late-onset diseases. This suggests that the RVIS can be used to prioritize genes based on their likelihood of causing disease. The study also explores the use of the RVIS in combination with variant-level scores, such as PolyPhen-2, to prioritize mutations. It finds that combining gene-level and variant-level information improves the ability to identify causal mutations. The RVIS is shown to be a useful tool for interpreting personal genomes and identifying pathogenic mutations.