The first step is to align the raw sequencing reads to a reference genome. Algorithms like BWA (Burrows-Wheeler Aligner) or Bowtie are commonly used for read alignment.

Duplicate reads generated during the sequencing process can skew results. Duplicate removal is a common preprocessing step to eliminate these redundant reads. Adjust the quality scores of the bases in the reads to account for systematic errors introduced during the sequencing process. This step improves the accuracy of variant calling.

SNV Calling: Spot places in the genome where a single nucleotide varies, finding possible single nucleotide changes (SNPs) and other small differences. Indel Calling: Find insertions or deletions in the genome, potentially causing a shift in the gene expression reading frame.

Variant Quality Score Recalibration helps in filtering out false positives and improves the overall accuracy of the variant calls. We filter variants based on various criteria such as read depth, mapping quality, and strand bias to remove low-confidence variants.

Functional Annotation: Annotate the identified variants to understand their potential functional impact. This involves predicting the consequences of variants on genes, proteins, and regulatory elements. Genix uses in house built annotation tools.

Combine information from multiple samples if applicable, especially in the context of studying populations or familial genetics. Collaborate with clinicians and geneticists to interpret the biological and clinical relevance of identified variants