SNP-array profiling data from breast cancer patients and healthy women's blood DNA samples

Breast cancer is commonly acknowledged as the primary type of cancer on a global scale, exerting a substantial influence on death rates, particularly in developing countries. The aforementioned discovery provides evidence in favor of the concept that genetic factors may contribute to the onset of breast cancer. This paper presents the unprocessed idat data containing single nucleotide polymorphisms (SNPs) acquired from breast cancer patients and a control group comprising of healthy women. The DNA was obtained from stored blood samples that were collected from a total of 48 female patients diagnosed with breast cancer at Cipto Mangunkusumo National Hospital Jakarta and Dharmais National Cancer Center Hospital Jakarta. Additionally, 24 healthy women were included as control subjects. Subsequently, the DNA samples were subjected to hybridization onto Infinium Asian Screening Array (ASA)'s beadchips. The chip was then subjected to fluorescence intensity measurements using an iScan machine manufactured by Illumina. The data output is produced in the form of a .idat file for each sample. Subsequently, further quality control measures and population stratification analysis were conducted using PLINK (v1.9). After the conclusion of the quality control procedure, 72 individuals and a dataset consisting of 424,285 genetic variants were selected for further analysis. The idat raw data files have been added to the Gene Expression Omnibus (GEO) with accession number: GSE245794 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE245794)<i>.</i>

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Publication Details

Journal
Data in Brief
Published
2025-01-27
DOI
https://doi.org/10.1016/j.dib.2025.111343
Citations
1
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
1.82

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article

SNP-array profiling data from breast cancer patients and healthy women's blood DNA samples

Sonar Soni Panigoro, Rafika Indah Paramita, Septelia Inawati Wanandi, Fadilah Fadilah et al.
1 citations
Data in Brief
Genetic Associations and Epidemiology
1.82
article

SNP-array profiling data from breast cancer patients and healthy women's blood DNA samples

Sonar Soni Panigoro, Rafika Indah Paramita, Septelia Inawati Wanandi, Fadilah Fadilah, Noorwati Sutandyo
article en
1 citations

Abstract

Breast cancer is commonly acknowledged as the primary type of cancer on a global scale, exerting a substantial influence on death rates, particularly in developing countries. The aforementioned discovery provides evidence in favor of the concept that genetic factors may contribute to the onset of breast cancer. This paper presents the unprocessed idat data containing single nucleotide polymorphisms (SNPs) acquired from breast cancer patients and a control group comprising of healthy women. The DNA was obtained from stored blood samples that were collected from a total of 48 female patients diagnosed with breast cancer at Cipto Mangunkusumo National Hospital Jakarta and Dharmais National Cancer Center Hospital Jakarta. Additionally, 24 healthy women were included as control subjects. Subsequently, the DNA samples were subjected to hybridization onto Infinium Asian Screening Array (ASA)'s beadchips. The chip was then subjected to fluorescence intensity measurements using an iScan machine manufactured by Illumina. The data output is produced in the form of a .idat file for each sample. Subsequently, further quality control measures and population stratification analysis were conducted using PLINK (v1.9). After the conclusion of the quality control procedure, 72 individuals and a dataset consisting of 424,285 genetic variants were selected for further analysis. The idat raw data files have been added to the Gene Expression Omnibus (GEO) with accession number: GSE245794 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE245794)<i>.</i>

Data in BriefVol. 59
University of Indonesia (ID), Dharmais Cancer Hospital (ID)
Kementerian Pendidikan dan Kebudayaan
Gender equality
Openalex Percentile: Top 19%
Genetic Associations and Epidemiology
1.82
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