- Separation studio version 3.00 build 15 illustrator cc software#
- Separation studio version 3.00 build 15 illustrator cc series#
The x-axis is the normalized θ, which is computed as θ = 2 π a r c t a n ( 1 A B ). ( B) The same cluster plot presented in polar coordinates. The y-axis is the normalized intensity for allele B. The x-axis is the normalized intensity for allele A.
( A) The cluster plot presented in Cartesian coordinates. An example of the benefit for using a QC cluster file is presented in Figure 1. This improvement is of particular importance for rare variants, which are often included on the latest generations of the genotyping platforms. Using a cluster file that has already been quality controlled significantly reduces the chance of miss-clustering and improves the call rate of samples. The cluster file can be exported from other genotyping projects of the same array design that has already been subjected to rigorous QC. While loading the data, an option is given of including a previous available cluster file. Instead, multiple sample sheets can be merged into one sheet to load all samples at once. GenomeStudio only permits one sample sheet to be loaded at a time, which is vastly inefficient. Generally, each sample sheet can contain up to 96 samples (96 samples per plate). The first step of analyzing Illumina genotyping data is to load the raw data into GenomeStudio, which can be a tedious process for large projects with hundreds of sample sheets. Here, we will describe detailed strategies for the processing and QC of Illumina genotyping arrays from multiple perspectives. Various QC procedures can be performed at both the GenomeStudio and PLINK level. Quality control has always been a major component in high-throughput genomic data processing, and thorough QC at multiple steps of data processing is necessary to ensure data integrity. The Genotyping Module of GenomeStudio processes the Illumina genotyping array from raw data to PLINK format, which is the standard format for storing genotyping data. There are no alternative methods for processing Illumina genotyping array currently.
Separation studio version 3.00 build 15 illustrator cc software#
GenomeStudio is an Illumina-designed software that processes their raw genomic data. The processing and QC of Illumina genotyping arrays can be divided into two major stages based on the primary tools used: GenomeStudio and PLINK. With the affordable price, excellent SNP content and customizability, the MEGA EX array is poised to become the next popular genotyping platform for large-scale genetic association studies. The exome arrays have quickly become popular and power many high-profile genetic and association studies. Compared with the cost of $600–$700 of exome sequencing per sample, the exome chip offers a much more fiscally reasonable alternative for conducting large-scale GWASs. The most attractive feature of these new Illumina arrays is their affordability, with prices at $55–$70 per array. With a substantial portion (68%) of the SNPs on exome arrays being rare, with minor allele frequency (MAF) 2 million SNPs and covers 65.7% of GWAS catalog SNPs.
Separation studio version 3.00 build 15 illustrator cc series#
One of Illumina’s newest series of products is the exome array with ∼240 000 SNPs, which, depending on the version, focuses on exonic variants, with an additional 24.8% of the SNPs from the GWAS catalog.
Illumina has a long history of designing and producing genotyping arrays, with many of them powering important GWAS. Genotyping microarrays are also referred to as single-nucleotide polymorphism (SNP) arrays, and have been the tool of choice for genome-wide association studies (GWASs) for the past 15 years. However, the decline of the gene expression microarray has coincided with a rising market for genotyping arrays thanks to new strategies and products set forth by Illumina. HTS-based RNA sequencing offers competitive prices and numerous analytical advantages, such as the ability to detect structural variants and novel transcripts. However, since the introduction of high-throughput sequencing (HTS), the application of gene expression quantification by microarray has gradually diminished. One of the early representative high-throughput genomic technologies is the microarray, which was the dominate technology for gene expression quantification and genotyping. High-throughput genomic technology has revolutionized the landscape of biomedical research.