#Evidence-Based Variant Interpretation and Clinical Exome Sequencing Applications
1Garen Haryanyan

1Gen-Era Diagnostics, Bioinformatic Team.

##Introduction

Clinical Exome Sequencing (CES) is a novel method of introducing the clinical etiology of human diseases into clinical routine tests with the help of next-generation sequencing technology.
When compared to its closest technique, Whole Exome Sequencing (WES), the most important difference of clinical exome sequencing is that it targets the regions that are clinically significant in the genome rather than sequencing the whole exome. It can be a standardized method that can be routinely used in genetic diagnosis instead of disease-specific sequencing panels.
In addition to the diagnosis with CES, genetic variations, which are reliable markers in the classification, prognosis, and treatment of the disease can be targeted.
The limitations encountered in CES and WES are:

- How much of the genes are covered?
- Interpretation and verification of the detected variants

The widespread use of CES can minimize these limitations by standardizing wet-lab practices and ease the bioinformatic analysis approaches used in variant interpretation and reporting across test centers. 

##Analysis of CES Data

The obtained genomic data are unique for each individual and very comprehensive to analyze. For this purpose, a strategic approach is generally more effective. The strategy to be developed should be unique to the individual or be based on the phenotype. The detailed clinical information required for strategy should be shared with the person who will perform the analysis, otherwise, it may change or prolong the diagnosis process. Information required for analysis and interpretation of the variant as follows:

- Family history
- Pedigree
- Sex
- Date of Birth / Onset
- Phenotype information (physical, neurological, cardiological, metabolic, etc.)
- Expected inheritance model

Any missing information extends the data analysis period as well as the ability to find the clinically significant variants.
While developing the analysis strategy, this clinical guidance is utilized and the variants identified in the patient are filtered step by step accordingly. Basic filtering steps start with filtering the genes associated with certain diseases or phenotypes can be used in the filtering process. In the following steps, other features such as coding transcript consequence (missense, nonsense, frameshift, splice), distance to an exon, allele frequency, and zygosity can be used. The remaining variants should be further examined through manual inspection based on current clinical literature, clinical databases, and guidelines.