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Hap550

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The Hap550 is a high-throughput gene expression profiling system that utilizes microarray technology to measure the expression levels of thousands of genes simultaneously. It is designed to provide accurate and reliable gene expression data for a variety of applications, including genomic research, drug discovery, and disease diagnosis.

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Lab products found in correlation

Infinium 1.2m, by Illumina (2 mentions) 660w quad, by Illumina (2 mentions) Humanomniexpress beadchip kit, by Illumina (1 mentions)

Spelling variants of this product

Human-Hap550 SNP array (2 citations)

3 protocols using hap550

1

Endometrial Cancer Genetics: UK Cohorts

Cited 1 time
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The National Study of Endometrial Cancer Genetics (NSECG) consisted of 925 histologically confirmed endometrial cancer cases from the UK; 86% with endometrioid-only histology. Genotyping was done using Illumina 660W Quad arrays.
These cases were matched with 1,286 cancer-free controls from the UK1/CORGI12 (link) and SP111 (link) colorectal studies genotypedusing Illumina Hap550, Hap300 and Hap240S arrays, and. 1958 Birth Cohort55 (link) controls from the Wellcome Trust Case Control Consortium (WTCCC2)13 (link) genotyped using Illumina Infinium 1.2M arrays.
Cheng T.H., Thompson D.J., O’Mara T.A., Painter J.N., Glubb D.M., Flach S., Lewis A., French J.D., Freeman-Mills L., Church D., Gorman M., Martin L., Hodgson S., Webb P.M., Attia J., Holliday E.G., McEvoy M., Scott R.J., Henders A.K., Martin N.G., Montgomery G.W., Nyholt D.R., Ahmed S., Healey C.S., Shah M., Dennis J., Fasching P.A., Beckmann M.W., Hein A., Ekici A.B., Hall P., Czene K., Darabi H., Li J., Dörk T., Dürst M., Hillemanns P., Runnebaum I., Amant F., Schrauwen S., Zhao H., Lambrechts D., Depreeuw J., Dowdy S.C., Goode E.L., Fridley B.L., Winham S.J., Njølstad T.S., Salvesen H.B., Trovik J., Werner H.M., Ashton K., Otton G., Proietto T., Liu T., Mints M., Tham E., Consortium C., Jun Li M., Yip S.H., Wang J., Bolla M.K., Michailidou K., Wang Q., Tyrer J.P., Dunlop M., Houlston R., Palles C., Hopper J.L., Peto J., Swerdlow A.J., Burwinkel B., Brenner H., Meindl A., Brauch H., Lindblom A., Chang-Claude J., Couch F.J., Giles G.G., Kristensen V.N., Cox A., Cunningham J.M., Pharoah P.D., Dunning A.M., Edwards S.L., Easton D.F., Tomlinson I, & Spurdle A.B. (2016). Five endometrial cancer risk loci identified through genome-wide association analysis. Nature genetics, 48(6), 667-674.
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2

Endometrial Cancer Genetics: UK Cohorts

Cited 1 time
Check if the same lab product or an alternative is used in the 5 most similar protocols
The National Study of Endometrial Cancer Genetics (NSECG) consisted of 925 histologically confirmed endometrial cancer cases from the UK; 86% with endometrioid-only histology. Genotyping was done using Illumina 660W Quad arrays.
These cases were matched with 1,286 cancer-free controls from the UK1/CORGI12 (link) and SP111 (link) colorectal studies genotypedusing Illumina Hap550, Hap300 and Hap240S arrays, and. 1958 Birth Cohort55 (link) controls from the Wellcome Trust Case Control Consortium (WTCCC2)13 (link) genotyped using Illumina Infinium 1.2M arrays.
Cheng T.H., Thompson D.J., O’Mara T.A., Painter J.N., Glubb D.M., Flach S., Lewis A., French J.D., Freeman-Mills L., Church D., Gorman M., Martin L., Hodgson S., Webb P.M., Attia J., Holliday E.G., McEvoy M., Scott R.J., Henders A.K., Martin N.G., Montgomery G.W., Nyholt D.R., Ahmed S., Healey C.S., Shah M., Dennis J., Fasching P.A., Beckmann M.W., Hein A., Ekici A.B., Hall P., Czene K., Darabi H., Li J., Dörk T., Dürst M., Hillemanns P., Runnebaum I., Amant F., Schrauwen S., Zhao H., Lambrechts D., Depreeuw J., Dowdy S.C., Goode E.L., Fridley B.L., Winham S.J., Njølstad T.S., Salvesen H.B., Trovik J., Werner H.M., Ashton K., Otton G., Proietto T., Liu T., Mints M., Tham E., Consortium C., Jun Li M., Yip S.H., Wang J., Bolla M.K., Michailidou K., Wang Q., Tyrer J.P., Dunlop M., Houlston R., Palles C., Hopper J.L., Peto J., Swerdlow A.J., Burwinkel B., Brenner H., Meindl A., Brauch H., Lindblom A., Chang-Claude J., Couch F.J., Giles G.G., Kristensen V.N., Cox A., Cunningham J.M., Pharoah P.D., Dunning A.M., Edwards S.L., Easton D.F., Tomlinson I, & Spurdle A.B. (2016). Five endometrial cancer risk loci identified through genome-wide association analysis. Nature genetics, 48(6), 667-674.
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3

Evaluating ABO and Rh Prediction Methods

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The first goal for testing our method was the collection of samples with phenotype annotation and genetic data. We chose to work with public data from the PGP [3 (link),4 (link)], mainly due to the richness of the clinical profiles. From the 2,651 profiles accessed on 13 May 2013, entries having ABO and Rh annotation with sequencing data were extracted. We obtained two datasets with 69 samples with full genome sequences from Complete Genomics and 111 with 23andMe SNP data. The nature of the 23andMe data set is very heterogeneous in array size (ranging from 570k to 1000k SNVs) and chip type (customized Illumina Hap550+ or HumanOmniExpress BeadChip Kit). The reference genome used was either hg18 or hg19. For a detailed description of the data, please refer to the PGP website (URL: http://personalgenomes.org/). The full genome dataset was used for benchmarking the accuracy of the tool for ABO and Rh when full data is available. The 23andMe dataset was used as a further set to evaluate our prediction strategy when only partial information is available.
Giollo M., Minervini G., Scalzotto M., Leonardi E., Ferrari C, & Tosatto S.C. (2015). BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data. PLoS ONE, 10(4), e0124579.
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