The raw data of GSE85195 [10 (link)] and GSE25099 [11 (link)] were downloaded from Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/ ) and processed using R software (4.0.5). Agilent's microarray sequencing chip was used in GSE85195; the sample type was Homo sapiens tissue samples; and the sequencing platform was the GPL6480 (Agilent-014850 Whole Human Genome Microarray 4 × 44 K G4112 F). The samples included 1 normal tissue, 15 OLK tissues, and 34 OSCC tissues. Affymetrix's microarray sequencing chip was used in GSE25099; the sample type was Homo sapiens tissue samples; and the sequencing platform was the GPL5175 (Affymetrix Human Exon 1.0 ST Array). The samples included 22 normal tissues and 57 OSCC tissues. The detailed information is shown in Table 1 . The normalizeBetweenArrays function of the limma package [12 (link)] and the RMA method of the affy [13 (link)] package was used to perform data standardization, normalization, and gene annotation, remove probes without annotation information, take the average expression when the same probe appears multiple times, and take the common gene combined data in the two datasets. The ComBat method of the sva package [14 (link)] was used to remove batch effects between multiple datasets to obtain a gene expression matrix.
Agilent 014850 whole human genome microarray 4
Manufactured by Agilent Technologies
The Agilent-014850 Whole Human Genome Microarray 4 × is a high-density microarray designed for whole-genome gene expression analysis. It enables the measurement of expression levels for over 27,000 human genes and transcripts across the entire human genome.
Automatically generated - may contain errors
4 protocols using agilent 014850 whole human genome microarray 4
1
Analyzing Gene Expression Profiles in Oral Carcinogenesis
2
Ovarian Cancer Transcriptomic Analysis
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The RNA-sequence profiles and corresponding clinical data of 581 patients with ovarian cancer were downloaded from TCGA (https://portal.gdc.cancer.gov/ ) (n = 364) and GEO (https://www.ncbi.nlm.nih.gov/geo/ ) (GSE17260, n = 110; GSE73614, n = 107). Both GEO datasets were based on the GPL6480 platform (Agilent-014850 Whole Human Genome Microarray 4 × 44 K G4112F). The ovarian cancer samples downloaded from the TCGA and GEO databases in this study are of primary ovarian tumors and do not contain borderline tumors. To eliminate differences between batches, we used the “sva” package in R software for normalization. We obtained 16,889 common genes for subsequent analyses. Additional file 2 : Table S1 shows the clinical characteristics of 581 patients with ovarian cancer. We randomly assigned the cohort into a training set (n = 292), which we used to build our predictive model, and a test set (n = 289) to verify the model.
3
Comparative Analysis of Intracranial Aneurysm and Periodontitis Gene Expression
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First we show the flow chart of this study (Fig. 1 ). The expression data of IAs and PDs were obtained from the GEO data base (https://www.ncbi.nlm.nih.gov/geo ). The search strategy for this study included: (1) subject searches for “intracranial aneurysms” and “periodontitis”, respectively; (2) Study type option selection “Expression profiling by array”; (3) samples were obtained from Homo sapiens; (4) the dataset contained normal control group samples. The mRNA sequencing of the data set GSE54083 was based on GPL4133 Agilent-014850 Whole Human Genome Microarray 4 × 44 K G4112F (Feature Number version). The mRNA sequencing of GSE10334 samples was based on GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0. The former includes 8 ruptured intracranial aneurysms samples, 5 unruptured aneurysm samples and 10 Superficial temporal artery samples, but the ruptured intracranial aneurysms samples will be excluded in this study. The latter contains 183 PD-affected gingival tissue samples and 64 unaffected gingival tissue samples.
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The flow diagram for the whole study
4
Integrative Analysis of Hypoxia and Ferroptosis in Cervical Cancer
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The cervical cancer gene expression data sets GSE7803, GSE63514 and GSE138080 were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/ ). The GSE7803 data set, including 24 normal and 28 cancer samples, was derived from the GPL96 platform in the [HG‐U133A] Affymetrix Human Genome U133A Array. The GSE63514 data set, including 10 normal and 24 cancer samples, was derived from the GPL570 platform of the [HG‐U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array. The GSE138080 data set, including 10 normal samples and 10 cancer samples, was derived from the GPL4133 platform of the Agilent‐014850 Whole Human Genome Microarray 4 × 44 K G4112F. Hypoxia‐related gene sets were acquired from the Molecular Signatures Database (MSigDB; https://www.gsea‐msigdb.org/gsea/msigdb/index.jsp ). Seven priority hypoxia‐related gene sets were eventually determined: hallmark hypoxia, reactome cellular response to hypoxia, Buffa hypoxia, Harris hypoxia, Mizukami hypoxia up, Mizukami hypoxia down and winter hypoxia metagenes. Ferroptosis‐related gene sets were acquired from the FerrDb V2 Database (http://www.zhounan.org/ferrdb/current/ ). We downloaded driver, suppressor and marker genes for ferroptosis. After removing duplicates, 493 hypoxia‐related and 464 ferroptosis‐related genes were identified for subsequent analyses.
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