Snp 6.0 array

Manufactured by Thermo Fisher Scientific

Sourced in United States, United Kingdom

The SNP 6.0 array is a high-density genotyping microarray developed by Thermo Fisher Scientific. It is designed to detect over 906,000 single nucleotide polymorphisms (SNPs) and over 946,000 probes for the detection of copy number variation (CNV) across the human genome. The SNP 6.0 array provides comprehensive genome-wide coverage for genetic analysis applications.

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Genome-Wide Human SNP 6.0 array (52 citations) 6.0 array (32 citations) SNP 6.0 (30 citations) SNP Array 6.0 (27 citations) Genome-Wide Human SNP Array 6.0 chip (17 citations) Genome-Wide Human SNP Array 6.0 platform (10 citations) SNP 6.0 array platform (8 citations) Genome-Wide SNP 6.0 array (7 citations) Affymetrix SNP 6.0 arrays (6 citations) Affymetrix 6.0 SNP Array (6 citations)

95 protocols using snp 6.0 array

Chromosomal Copy Number Variant Detection

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Tumour DNA was isolated using the QIAmp DNA Mini kit (Qiagen, Venlo, The Netherlands). Single-nucleotide polymorphism (SNP) analysis was performed using an Affymetrix 250K_NSP or Affymetrix SNP 6.0 array to detect chromosome 3 loss. Additional copies of chromosome 8q were detected by Affymetrix SNP 6.0 array and analyzed using the GISTIC 2.0 algorithm [20 (link),21 (link)].

Souri Z., Jochemsen A.G., Wierenga A.P., Kroes W.G., Verdijk R.M., van der Velden P.A., Luyten G.P, & Jager M.J. (2021). Expression of HDACs 1, 3 and 8 Is Upregulated in the Presence of Infiltrating Lymphocytes in Uveal Melanoma. Cancers, 13(16), 4146.

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Comprehensive Genomic Profiling Pipeline

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DNA was hybridized onto Affymetrix SNP 6.0 arrays and normalized as previously described^{6 (link)}. Segmentation was performed using Circular Binary Segmentation algorithm⁵⁶ followed by Ziggurat Deconstruction to infer the length and amplitude each segment. Recurrent focal SCNA peaks were identified using GISTIC2.0⁵⁷. A peak was considered focally amplified or deleted within a tumor if the GISTIC2.0-estimated focal copy number ratio was greater than 0.1 or less than −0.1, respectively. Purity and ploidy were estimated using ABSOLUTE⁵⁴. Two peaks were considered the same across tumor types if 1) the known target gene of each peak was the same or 2) the genomic location of the peaks overlapped +/− 1 Mb and each of the overlapping peaks had less than 25 genes and was smaller than 10 Mb.

Campbell J.D., Alexandrov A., Kim J., Wala J., Berger A.H., Pedamallu C.S., Shukla S.A., Guo G., Brooks A.N., Murray B.A., Imielinski M., Hu X., Ling S., Akbani R., Rosenberg M., Cibulskis C., Ramachandran A., Collisson E.A., Kwiatkowski D.J., Lawrence M.S., Weinstein J.N., Verhaak R.G., Wu C.J., Hammerman P.S., Cherniack A.D., Getz G., Artyomov M.N., Schreiber R., Govindan R, & Meyerson M. (2016). Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nature genetics, 48(6), 607-616.

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Comprehensive Genomic Profiling of TCGA Samples

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For 10,522 TCGA samples, somatic DNA copy number was determined from Affymetrix SNP 6.0 arrays. For 9,670 of these 10,522 samples, RSEM (relative standard error of the mean) expression values were determined from Illumina mRNA sequencing data. For 9,756 of these 10,522 samples, mutations were called from whole-exome DNA sequencing data (TCGA MC3 manuscript, in preparation). (See also Table S1.)

Taylor A.M., Shih J., Ha G., Gao G.F., Zhang X., Berger A.C., Schumacher S.E., Wang C., Hu H., Liu J., Lazar A.J., Cherniack A.D., Beroukhim R, & Meyerson M. (2018). Genomic and Functional Approaches to Understanding Cancer Aneuploidy. Cancer cell, 33(4), 676-689.e3.

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Comprehensive Tumor Genome Analysis

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DNA from each tumor or germline sample was hybridized to Affymetrix SNP 6.0 arrays. For each tumor, genome-wide copy number estimates were refined using tangent normalization, in which tumor signal intensities are divided by signal intensities from the linear combination of all normal samples that are most similar to the tumor. Significant focal copy number alterations were identified from segmented data using GISTIC 2.0. Allelic copy number, regions of homozygous deletions, whole genome doubling and purity and ploidy estimates were calculated using the ABSOLUTE algorithm.

Cherniack A., Shen H., Walter V., Stewart C., Murray B., Bowlby R., Hu X., Ling S., Soslow R.A., Broaddus R.R., Zuna R.E., Robertson G., Laird P.W., Kucherlapati R., Mills G.B., Weinstein J.N., Zhang J., Akbani R, & Levine D.A. (2017). Integrated Molecular Characterization of Uterine Carcinosarcoma. Cancer cell, 31(3), 411-423.

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TCGA Analysis of Uterine Corpus Endometrial Carcinoma

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All data were extracted and analyzed from The Cancer Genome Atlas (TCGA) consortium’s sequencing of Uterine Corpus Endometrial Carcinoma (UCEC) patient-tumor pairs, as maintained in the UCSC Cancer Genome Browser. The provisional dataset of 548 tumors, 242 of which had both CNA and mutation data, were downloaded and analyzed for this study. TP53 mutant tumors were identified as those annotated with a p53 mutation in cBioPortal [44 (link)], which were 68 tumors. The total fraction of the genome altered (Fig 5C) were downloaded from the curated values within the clinical characteristics in cBioPortal, as were survival data. Survival curves compared patients with 16q13, 9q34, or 15q24 losses (cadmium response regions), or those without these losses, independent of p53 status. TCGA copy number signals were generated on Affymetrix SNP 6.0 arrays and run through the Broad Institute pipeline [58 (link)] to determine CNVs, and we used these data as curated by the UCSC Cancer Genome Browser [59 (link)]. GISTIC2 copy number calls were used to assess allelic losses [10 (link)]. SNP data were input into the Integrated Genomics Viewer [60 (link)] to generate the loss/amplification panels of PMCH and PMCL tumors in Fig 1.

Delaney J.R, & Stupack D.G. (2016). Whole Genome Pathway Analysis Identifies an Association of Cadmium Response Gene Loss with Copy Number Variation in Mutant p53 Bearing Uterine Endometrial Carcinomas. PLoS ONE, 11(7), e0159114.

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Genetic Ancestry Analysis of TCGA Breast Cancer Patients

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DNA samples from blood or normal breast were genotyped using Affymetrix SNP 6.0 arrays. For patients with both blood and normal breast samples, we utilized the genotype data from blood only. Uncorrelated single nucleotide polymorphisms from the TCGA cohort and the International HapMap Project were included in the principal component analysis. The top two eigenvectors from principal component analysis were plotted and the three known continental ancestry groups from the HapMap were used as anchors. The proportion of ancestry relative to the reference continental groups for each patient was estimated by projecting the eigenvectors onto each of the three axes defined by the three anchors. The genetic ancestry information of breast cancer patients from TCGA was obtained from our previous study^{6 (link)}. Briefly, we estimated the ancestry of breast cancer patients from TCGA using principal component analysis. According to the estimated proportion of ancestry, patients were grouped into genomic Black (≥50% African ancestry), genomic White (≥90% European ancestry), and genomic Asian (≥90% Asian ancestry). All Nigerian patients were assumed to be 100% African with little to no admixture with other populations.

Ansari-Pour N., Zheng Y., Yoshimatsu T.F., Sanni A., Ajani M., Reynier J.B., Tapinos A., Pitt J.J., Dentro S., Woodard A., Rajagopal P.S., Fitzgerald D., Gruber A.J., Odetunde A., Popoola A., Falusi A.G., Babalola C.P., Ogundiran T., Ibrahim N., Barretina J., Van Loo P., Chen M., White K.P., Ojengbede O., Obafunwa J., Huo D., Wedge D.C, & Olopade O.I. (2021). Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes. Nature Communications, 12, 6946.

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Tumor Purity and Ploidy Estimation

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This dataset included 1,992 pairs of expression arrays and Affymetrix SNP 6.0 arrays profiled for tumor samples from 1,992 patients, which was divided into a discovery set (997 patients) and a validation set (995 patients)^{38 (link)}. A total of 144 expression arrays for adjacent normal tissues were provided.
We applied the DeMixT deconvolution pipeline to the expression arrays of the combined discovery and validation sets, after batch effect correction, to estimate tumor-specific proportions using the adjacent normal samples as the reference. Affymetrix CEL files were processed by PennCNV^{87 (link)} to obtain the LogR and B allele frequency (BAF) data, followed by both ASCAT^{32 (link)} and Sequenza^{49 (link)} to estimate tumor purity and ploidy for each sample. The consensus TmS strategy was applied to obtain robust TmS estimations. In total, 1,664 patient samples with TmS remained after the above steps. We additionally removed 118 patient samples due to missing follow-up information of biochemical recurrence intervals or the PAM50 subtypes. A final cohort of 1,546 patient samples from both the discovery and validation sets was kept for downstream analyses. See Supplementary Notes 2.3.1 and 2.3.4 for further details.

Cao S., Wang J.R., Ji S., Yang P., Dai Y., Guo S., Montierth M.D., Shen J.P., Zhao X., Chen J., Lee J.J., Guerrero P.A., Spetsieris N., Engedal N., Taavitsainen S., Yu K., Livingstone J., Bhandari V., Hubert S.M., Daw N.C., Futreal P.A., Efstathiou E., Lim B., Viale A., Zhang J., Nykter M., Czerniak B.A., Brown P.H., Swanton C., Msaouel P., Maitra A., Kopetz S., Campbell P., Speed T.P., Boutros P.C., Zhu H., Urbanucci A., Demeulemeester J., Van Loo P, & Wang W. (2022). Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression. Nature Biotechnology, 40(11), 1624-1633.

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Comprehensive Genomic Profiling of Cancers

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Cell-lines were analyzed with Affymetrix SNP6.0 arrays. PICNIC (32 (link)) was used for normalization and integer copy number estimation.
TCGA Affymetrix SNP6.0 data were downloaded for 422 CRC, 898 Breast, 391 Lung (Ad), 407 Lung (SC), 506 Ovarian and 503 Renal cancers (http://tcga.data.nci.nih.gov/tcga/). Samples that failed Affymetrix Genotyping Console QC were excluded. LogR and BAFs were obtained using the aroma R package (33 (link)). Integer copy numbers were estimated using OncoSNP (34 (link)).
Validation cohort analysis was performed on Illumina 610 Quad arrays. LogRs and BAFs were obtained using GenomeStudio V2011.1 and Genotyping Module V1.9.4. For QC, samples with moving standard deviation >0.28 were discarded. Integer copy numbers were estimated using OncoSNP (34 (link)).
Ploidy was estimated for each sample by summing the weighted median integer copy for each chromosome and dividing by number of chromosomes analyzed (n=22). The number of chromosomes in each sample was estimated by summing the modal copy numbers from the segmented copy number profile of each chromosome. Each segment was weighted according to the number of base pairs it covered. Copy number segments of loss and gain were defined relative to ploidy. wGII was calculated as in (23 (link)).

Dewhurst S.M., McGranahan N., Burrell R.A., Rowan A.J., Grönroos E., Endesfelder D., Joshi T., Mouradov D., Gibbs P., Ward R.L., Hawkins N.J., Szallasi Z., Sieber O.M, & Swanton C. (2014). Tolerance whole of genome doubling propagates chromosomal instability and accelerates cancer genome evolution. Cancer discovery, 4(2), 175-185.

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Genomic DNA Sequencing and Variant Analysis

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Genomic DNA was isolated from frozen tissues using the Qiagen DNAamp kit or a standard proteinase K protocol. Samples were sequenced on an Illumina HiSeq-2000 to an average of 77× depth (85.6% targeted reads > 20× coverage). The average rate of read alignment was 98.6%. Affymetrix SNP 6.0 arrays were used for a subset of samples. Seven CAHs, out of 19 profiled, were found to have both an exceptionally low purity (less than 25% per ABSOLUTE analysis²³) and low burden of mutations. Upon manual review, the mutations whose allelic fractions were higher than 10% were enriched in regions with low mapping quality. These seven samples were therefore excluded from further analyses.

Gibson W.J., Hoivik E.A., Halle M.K., Taylor-Weiner A., Cherniack A.D., Berg A., Holst F., Zack T.I., Werner H.M., Staby K.M., Rosenberg M., Stefansson I.M., Kusonmano K., Chevalier A., Mauland K.K., Trovik J., Krakstad C., Giannakis M., Hodis E., Woie K., Bjorge L., Vintermyr O.K., Wala J.A., Lawrence M.S., Getz G., Carter S.L., Beroukhim R, & Salvesen H.B. (2016). The genomic landscape and evolution of endometrial carcinoma progression and abdominopelvic metastasis. Nature genetics, 48(8), 848-855.

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Genome-wide SNP Analysis of Cell Lines

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We performed genome wide single nucleotide polymorphism (SNP) analysis using SNP 6.0 arrays (Affymetrix, High Wycombe, U.K) on SKM1-S and SKM1-R cell lines. DNA was prepared for hybridization according to the manufacturers' recommendations. Affymetrix CEL files for each sample were analyzed using the Genotyping Console software (v3.0.2). Genotyping was performed using Birdseed V2 algorithm. Unpaired Copy Number and LOH analysis was performed with Regional GC correction. Copy number and UPD were also analyzed using the Copy Number Analyzer for GeneChip (CNAG version 3.3.0.1) algorithm (http://www.genome.umin.jp/CNAGtop2.html) [28 (link)].

Cluzeau T., Dubois A., Jacquel A., Luciano F., Renneville A., Preudhomme C., Karsenti J.M., Mounier N., Rohrlich P., Raynaud S., Mari B., Robert G, & Auberger P. (2014). Phenotypic and genotypic characterization of azacitidine-sensitive and resistant SKM1 myeloid cell lines. Oncotarget, 5(12), 4384-4391.

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