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Mcl-1 is a key determinant of breast cancer cell survival [copy number]

ABSTRACT: Copy number profile of cultured Breast Cancer cell line measured by Affymetrix SNPs microarrays

ORGANISM(S): Homo sapiens

PROVIDER: GSE66070 | GEO | 2015/08/07

SECONDARY ACCESSION(S): PRJNA275814

REPOSITORIES: GEO

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Mcl-1 is a key determinant of breast cancer cell survival [copy number]

Project description:Copy number profile of cultured Breast Cancer cell line measured by Affymetrix SNPs microarrays Whole genome copy number profile of 2 breast cancer cell lines were analyzed using Affymetrix SNP6.0 arrays

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Mcl-1 is a key determinant of breast cancer cell survival [expression]

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Mcl-1 is a key determinant of breast cancer cell survival [expression]

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Mcl-1 is a key determinant of breast cancer cell survival

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

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Mcl-1 is a key determinant of breast cancer cell survival

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Copy Number Variation data from non-trasformed human fibroblasts

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Project description:Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis and public release of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with geographic distance from Africa, as expected under a serial founder effect for an out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected—including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas—the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations. Keywords: High Density SNP array

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