Background:The technical advances in sequencing made in less than a decade associated with the development and low costs of high throughput sequencing techniques allow their application in genomic medicine. Therefore, Whole Exome Sequencing (WES), which corresponds to less than 2% of the entire genome, emerges as a cost-effective tool that aims to identify variants related to human diseases. Bioinformatics is fundamental to process the big volume of data and link the obtained results with the biology. Objective: We aim to apply and evaluate protocols and applications designed for WES data analysis on human subjects. We also intend to apply and enhance protocols and applications designed to predict variants as potentially pathological from WES data. Materials and Methods: We used the following tools: FastQC, Rqc, BWA, Picard, GATK e VEP. We applied them to exome data, determining variation in quality profiles, local realignment, quality recalibration and variant calls. We also evaluated whether or not technical and population differences affect the depth profiles of samples from the 1000 Genomes Project. Results: We applied our protocol on 27 samples, resulting in pre and postalignment quality control charts. Local realignment took place at more than 15% of the exome definition, extending to more than 79% of sequences. Quality recalibration minimized per cycle variation. In total, 72% of the sequences were paired against the genome, nevertheless 46% extended off-target. The mean coverage was 59X for the exome. We also detected that depth tends to vary based on technical and population differences between samples. Conclusion: We applied x a variant-calling workflow that accounts for sequence quality, the alignment against the genome, local realignment, quality recalibration and annotation. In addition, we concluded that depth depends on technical and population differences, showing that genomic complexity may interfere with the capturing phase, affecting downstream analyses.