Background: Hospitalized patients are at increased risk for candidemia and invasive candidiasis (C/IC). Improved therapeutic regimens with enhanced clinical and pharmacoeconomic outcomes utilizing existing antifungal agents are still needed.Methods: An ope

Exome and whole-genome analyses powered by next-generation sequencing (NGS) have become invaluable tools in identifying causal mutations responsible for Mendelian disorders. Given that individual exomes contain several thousand single nucleotide variants and insertions/deletions, it remains a challenge to analyze large numbers of variants from multiple exomes to identify causal alleles associated with inherited conditions. To this end, we have developed user-friendly software that analyzes variant calls from multiple individuals to facilitate identification of causal mutations. The software, termed exomeSuite, filters for putative causative variants of monogenic diseases inherited in one of three forms: dominant, recessive caused by a homozygous variant, or recessive caused by two compound heterozygous variants. In addition, exomeSuite can perform homozygosity mapping and analyze the variant data of multiple unrelated individuals. Here we demonstrate that filtering of variants with exomeSuite reduces datasets to a fraction of a percent of their original size. To the best of our knowledge this is the first freely available software developed to analyze variant data from multiple individuals that rapidly assimilates and filters large data sets based on pattern of inheritance.