Query: tell me if this is correct and give me cites 3.2 Technological Advancements and Methodologies
Next-generation sequencing (NGS) and genotyping technologies allow for comprehensive, high-throughput analyses
NGS has been transformative in allowing researchers to analyze entire genomes or targeted regions with unprecedented speed and accuracy. NGS has dramatically changed our understanding of our genome and ourselves11. This high-throughput technology facilitates studies that were previously unfeasible, such as large-scale association studies and fine-grained population structure analyses. 

Use of Microarrays and Sequencing to Identify Genetic Variants Linked to Diseases in Latin American Populations
Microarray technology has been a key tool in genomic research, allowing scientists to analyze hundreds of thousands of single nucleotide polymorphisms (SNPs) at a relatively low cost. In Latin America, microarrays have been instrumental in identifying genetic variants associated with diseases such as Type 2 diabetes, hypertension, and obesity. These insights have advanced understanding of how genetic diversity in the region influences disease susceptibility. However, a critical limitation of microarrays lies in their design, which often introduces ascertainment bias, a challenge that is particularly relevant when studying underrepresented populations like those in Latin America.
What is ascertainment bias?
Ascertainment bias in the context of microarrays arises from how the SNPs included in the array are selected. Typically, these SNPs are chosen based on their presence and variability in reference populations, which are predominantly of European ancestry. As a result, the genetic variants represented on the array may not fully capture the genetic diversity of non-European populations. For example, variants that are common in Indigenous, African, or mixed-ancestry populations in Latin America may be missing or poorly represented in commercially available microarrays, leading to incomplete or skewed analyses.
Custom SNP inclusion: A partial solution
Recognizing the limitations of standard microarrays, some companies now offer the ability to customize genotyping panels by adding a subset of user-specified SNPs. This feature enables researchers to include genetic variants that are particularly relevant to their target populations. For instance, custom panels can be designed to incorporate SNPs identified from whole-genome sequencing (WGS) of Indigenous or admixed individuals, ensuring better representation of Latin American genetic diversity.
Challenges with custom SNP panels
While adding custom SNPs is a step toward reducing ascertainment bias, it requires a priori information about which variants to include. This presents several challenges:
Need for comprehensive reference data: Researchers must first have access to high-quality datasets, such as those generated through WGS, to identify the variants of interest. In Latin America, where many populations still need to be represented in genomic studies, obtaining this data can take time and effort.
Bias in variant selection: Even with custom SNPs, the initial selection process may still overlook rare or novel variants that are yet to be discovered in local populations.
Resource constraints: Designing and validating custom panels increases both time and costs, making it less accessible to researchers with limited funding.
Reduction of sequencing cost
A major barrier to genomic research in Latin America has historically been the cost of sequencing. Over the past two decades, sequencing costs have plummeted, making these technologies more accessible to researchers worldwide. For example, the cost of sequencing a whole human genome has dropped from millions of dollars during the HGP era to just a few hundred dollars today. This democratization of sequencing has allowed more institutions in Latin America to engage in cutting-edge research, fostering collaboration and expanding the representation of Latin American populations in global genomic studies.
Subject: biology
Intent: Paper Understanding