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Affymetrix 6.0 snp array

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The Affymetrix 6.0 SNP Array is a high-density genotyping microarray designed to detect single nucleotide polymorphisms (SNPs) across the human genome. It contains probes for over 1.8 million genetic markers, including more than 906,600 SNPs and 946,000 probes for the detection of copy number variations.

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Lab products found in correlation

Genotyping console gtc 4, by Thermo Fisher Scientific (3 mentions) Genotyping console, by Thermo Fisher Scientific (2 mentions) Dneasy blood and tissue kit, by Qiagen (2 mentions)

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Affymetrix SNP 6.0 arrays Affymetrix 6.0 array SNP 6.0 arrays SNP Array 6.0 6.0 array SNP arrays SNP 6.0 Array 6.0

6 protocols using affymetrix 6.0 snp array

1

Affymetrix 6.0 SNP Array Genotyping

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DNA labelling, hybridization, and array scanning were performed with Affymetrix 6.0 SNP arrays (Affymetrix, Santa Clara, CA) according to the manufacturer's protocol and processed using Affymetrix Genotyping Console (GTC) 4.0 software. Data were processed as previously described [6 (link)]. When SNP 6.0 data was not available, copy number data were calculated based on the CGI relative coverage smoothed in 100-kb windows, corrected for the GC content, and normalized using composite baseline coverage from multiple healthy samples. Segments defined by a minimum of 8 probes with segment log2 mean <-0.5 or >+0.5 were considered lost and gained, respectively, unless otherwise indicated.
Gadd S., Huff V., Walz A.L., Ooms A.H., Armstrong A.E., Gerhard D.S., Smith M.A., Guidry Auvil J.M., Meerzaman D., Chen Q.R., Hsu C.H., Yan C., Nguyen C., Hu Y., Hermida L.C., Davidsen T., Gesuwan P., Ma Y., Zong Z., Mungall A.J., Moore R.A., Marra M.A., Dome J.S., Mullighan C.G., Ma J., Wheeler D.A., Hampton O.A., Ross N., Gastier-Foster J.M., Arold S.T, & Perlman E.J. (2017). A Children's Oncology Group and TARGET Initiative Exploring the Genetic Landscape of Wilms Tumor. Nature genetics, 49(10), 1487-1494.
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2

Affymetrix 6.0 SNP Array Genotyping

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DNA labelling, hybridization, and array scanning were performed with Affymetrix 6.0 SNP arrays (Affymetrix, Santa Clara, CA) according to the manufacturer's protocol and processed using Affymetrix Genotyping Console (GTC) 4.0 software. Data were processed as previously described [6 (link)]. When SNP 6.0 data was not available, copy number data were calculated based on the CGI relative coverage smoothed in 100-kb windows, corrected for the GC content, and normalized using composite baseline coverage from multiple healthy samples. Segments defined by a minimum of 8 probes with segment log2 mean <-0.5 or >+0.5 were considered lost and gained, respectively, unless otherwise indicated.
Gadd S., Huff V., Walz A.L., Ooms A.H., Armstrong A.E., Gerhard D.S., Smith M.A., Guidry Auvil J.M., Meerzaman D., Chen Q.R., Hsu C.H., Yan C., Nguyen C., Hu Y., Hermida L.C., Davidsen T., Gesuwan P., Ma Y., Zong Z., Mungall A.J., Moore R.A., Marra M.A., Dome J.S., Mullighan C.G., Ma J., Wheeler D.A., Hampton O.A., Ross N., Gastier-Foster J.M., Arold S.T, & Perlman E.J. (2017). A Children's Oncology Group and TARGET Initiative Exploring the Genetic Landscape of Wilms Tumor. Nature genetics, 49(10), 1487-1494.
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3

Genome-wide SNP Screening for Rare CNVs

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DNA was extracted from blood using DNeasy Blood and Tissue Kit (Qiagen Inc., Valencia, CA). Genome-wide SNP screening on the two affected individuals from Family 1 was performed using Affymetrix 6.0 SNP Array (Affymetrix, USA). SNP genotyping data was used to perform homozygosity and copy number analyses. Homozygosity mapping was performed as previously described35 (link). CNV analysis was performed using four algorithms in parallel (Birdsuite, PennCNV, Nexus and Affymetrix Genotyping Console), requiring a minimum of 10 probes and the concordance of at least two algorithms for specificity. To distinguish rare from common variation, results were matched against a catalog of reference CNVs generated via the same pipeline, using 1251 samples from the HapMap project (11 subpopulations, public release #3). For additional stringency, CNVs were further matched with CNVs present in the Database of Genomic Variants (DGV) as well as an internal database of CNVs from over 12000 unrelated research samples (including >1000 from the Middle East with a variety of neurodevelopmental conditions, and >105 healthy Saudi individuals).
Jamuar S.S., Schmitz-Abe K., D’Gama A.M., Drottar M., Chan W.M., Peeva M., Servattalab S., Lam A.T., Delgado M.R., Clegg N.J., Al Zayed Z., Dogar M.A., Alorainy I.A., Jamea A.A., Abu-Amero K., Griebel M., Ward W., Lein E.S., Markianos K., Barkovich A.J., Robson C.D., Grant P.E., Bosley T.M., Engle E.C., Walsh C.A, & Yu T.W. (2017). Biallelic Mutations In Human DCC Cause Developmental Split Brain Syndrome. Nature genetics, 49(4), 606-612.
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4

Affymetrix 6.0 SNP Array Analysis

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Nucleic acid labeling, hybridization, and array scanning were performed on 11 CCSKs according to the manufacturer's protocol for the Affymetrix 6.0 SNP array (Affymetrix, Santa Clara, CA, USA) and processed with the Affymetrix Genotyping Console (GTC) 4.0 software. Reference normalization was performed as described by Pounds et al [49 (link)]. Circular binary segmentation (CBS) was performed using DNAcopy from BioConductor (http://www.bioconductor.org). Segmented regions of autosomal chromosomes containing at least 8 markers in which the log2 value was > +0.5 or < −0.5 were considered regions of gain or loss, respectively. For the other 2 CCSK samples, copy number was assessed by using relative coverage generated by whole genome sequencing.
Gooskens S.L., Gadd S., Guidry Auvil J.M., Gerhard D.S., Khan J., Patidar R., Meerzaman D., Chen Q.R., Hsu C.H., Yan C., Nguyen C., Hu Y., Mullighan C.G., Ma J., Jennings L.J., de Krijger R.R., van den Heuvel-Eibrink M.M., Smith M.A., Ross N., Gastier-Foster J.M, & Perlman E.J. (2015). TCF21 hypermethylation in genetically quiescent clear cell sarcoma of the kidney. Oncotarget, 6(18), 15828-15841.
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5

Genome-wide SNP Screening for Rare CNVs

Cited 1 time
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DNA was extracted from blood using DNeasy Blood and Tissue Kit (Qiagen Inc., Valencia, CA). Genome-wide SNP screening on the two affected individuals from Family 1 was performed using Affymetrix 6.0 SNP Array (Affymetrix, USA). SNP genotyping data was used to perform homozygosity and copy number analyses. Homozygosity mapping was performed as previously described35 (link). CNV analysis was performed using four algorithms in parallel (Birdsuite, PennCNV, Nexus and Affymetrix Genotyping Console), requiring a minimum of 10 probes and the concordance of at least two algorithms for specificity. To distinguish rare from common variation, results were matched against a catalog of reference CNVs generated via the same pipeline, using 1251 samples from the HapMap project (11 subpopulations, public release #3). For additional stringency, CNVs were further matched with CNVs present in the Database of Genomic Variants (DGV) as well as an internal database of CNVs from over 12000 unrelated research samples (including >1000 from the Middle East with a variety of neurodevelopmental conditions, and >105 healthy Saudi individuals).
Jamuar S.S., Schmitz-Abe K., D’Gama A.M., Drottar M., Chan W.M., Peeva M., Servattalab S., Lam A.T., Delgado M.R., Clegg N.J., Al Zayed Z., Dogar M.A., Alorainy I.A., Jamea A.A., Abu-Amero K., Griebel M., Ward W., Lein E.S., Markianos K., Barkovich A.J., Robson C.D., Grant P.E., Bosley T.M., Engle E.C., Walsh C.A, & Yu T.W. (2017). Biallelic Mutations In Human DCC Cause Developmental Split Brain Syndrome. Nature genetics, 49(4), 606-612.
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6

Genome-wide SNP genotyping and imputation

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Genotyping for single nucleotide polymophisms (SNPs) was performed with the Affymetrix 6.0 SNP Array (Affymetrix, Santa Clara, Calif). Outliers based on principal components, sample swaps, duplicates, and one of each pair of monozygotic twins were excluded. Samples with a mismatch between pedigree vs genetic sex were also removed. Variants with a minor allele frequency ≥ 1%, a call rate ≥ 90%, and a Hardy Weinberg equilibrium (HWE) p-value >10–6 (n = 832,508 variants) were used for imputation to 1000 Genomes Project population SNP reference panel (Phase 3, Version 5), using Minimac3 on the Michigan Imputation Server. Only SNPs with an imputation quality r2>0.9 were selected for polygenic risk score analyses.
Anwar M.Y., Raffield L.M., Lange L.A., Correa A, & Taylor K.C. (2021). Genetic underpinnings of regional adiposity distribution in African Americans: Assessments from the Jackson Heart Study. PLoS ONE, 16(8), e0255609.
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