illumina的Omni系列芯片进化史

Jimmy

希望这个链接不要过时：https://www.illumina.com/Documen ... et_gwas_roadmap.pdf
也就是说，希望illumina公司不要倒闭！
Genome-wide association studies(GWAS) have identified hundreds ofcommon genetic variants associatedwith human diseases and providedvaluable insights into the geneticarchitecture behind many diseases.Building on this success, the 1,000Genomes Project (1KGP) is expectedto dramatically expand the catalog ofhuman genetic variants for the nextgeneration of GWAS, as the project willseek to identify nearly all variants thatexist at any appreciable frequency

Jimmy

芯片设计到的marker个数如下：

	Illumina Infinium HumanExome BeadChip 1.0	Affymetrix Genome Wide Human SNP Array 6.0	Illumina HumanOmni 1	Illumina Human Omni 2.5	Illumina Human Omni 5	Axiom Exome319
Total Number of Markers	242901	934969	1134514	2379855	4301332	319302
Indel	137	0	454	43	4537	35138
SNP	242764	934969	1134060	2379812	4296795	284164
Exonic	224571	8718	59791	62711	129338	269272
Intronic	5740	343502	365281	855282	1582445	12054
Intergenic	8561	533624	536971	1292448	2240454	19229
Others	4029	49125	172471	169414	349095	18747

Jimmy

illumina的外显子芯片跟真正的外显子测序比较起来：

首先是成本
At a cost of less than $50 per chip, exome chips have become cost-effective alternatives to exome sequencing for large GWASs. Furthermore, exome chip data require less hard drive space for storage and processing than exome sequencing data.
然后是数据量：
For an exome chip genotyping project of 39,000 samples, ∼3.6 TB of storage is required to store and process the data. If the same size study were done by exome sequencing, ∼400 TB storage space could be required.
最后是功效
However, exome sequencing enables researchers to identify novel SNPs across the whole exome region plus some intron and intergenic regions

Jimmy

数据分析方法如下：

GenomeStudio section 这个是illumina自己开发的软件

Loading the data into GenomeStudio
Performing automatic clustering
QC on SNPs located in a haploid genome
QC based on GenTrain score
QC based on cluster separation
QC based on Mendelian error and replication error
QC based on other criteria
Calling rare SNPs
Final fltering
Exporting from GenomeStudio

Post-GenomeStudio section还需要用其它软件

Converting all SNPs to the forward strand
Checking for gender mismatch
Checking for race mismatch
Checking for relatedness
Checking for Hardy-Weinberg equilibrium (HWE) outliers
Checking for heterozygosity outliers
Checking consistency between exome chip genotype and 1000 Genomes Project17 or HapMap18 genotype
Checking for minor allele frequency (MAF) consistency between exome chip and 1000 Genomes Project genotypes
Checking for batch effects

Jimmy

这篇文章可以看一看：Illumina human exome genotyping array clustering and quality control
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4441213

Jaylen

What about the manufacturing of biochip?