Two microarray‐based GE experiments were conducted on muscle obtained from the original cohort 14 . The first experiment used Agilent chips 14 . The second was performed in another set of individuals from that cohort. The overall GE analysis comprised a subset (Lean = 13, OIR = 11 and OIS = 11) which is the common subset of individuals where both transcriptomics and lipidomics data were available. GE profiles were obtained using both Affymetrix U133A and Agilent Whole Mouse Genome 4x44K array platforms. The relative mRNA levels for all transcripts across all subjects were studied. The raw Agilent data were pre‐processed 14 . GE measures obtained for ∼56K transcripts using the Affymetrix U133A array platform were pre‐processed using Robust Multi‐array Average (RMA) method 15 in the R‐programming environment.
U133a array
Manufactured by Thermo Fisher Scientific
The U133A arrays are high-density oligonucleotide microarray products designed for gene expression analysis. They provide comprehensive coverage of the human genome and enable the simultaneous measurement of the expression level of thousands of genes. The U133A arrays are a well-established and widely-used tool for transcriptome-wide studies.
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Lab products found in correlation
Ovation pico wta system v2, by Tecan (3 mentions)
Encore biotin module, by Tecan (3 mentions)
Laboratory on chip total rna picokit agilent bioanalyzer, by Agilent Technologies (2 mentions)
Rnalater reagent, by Qiagen (2 mentions)
Expression console, by Thermo Fisher Scientific (2 mentions)
Agilent 2100 bioanalyzer, by Agilent Technologies (2 mentions)
Rneasy kit, by Qiagen (2 mentions)
Hg u133 plus 2, by Thermo Fisher Scientific (1 mentions)
Genome u133 plus 2.0 array, by Thermo Fisher Scientific (1 mentions)
U133 plus 2.0 array, by Thermo Fisher Scientific (1 mentions)
17 protocols using u133a array
1
Muscle Transcriptome Analysis of Obesity
2
GBM Gene Expression Analysis
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The Test set (E-GEOD-13041) was obtained from http://www.ebi.ac.uk/arrayexpress/ and is a publically available gene expression dataset for patients with a diagnosis of GBM. This dataset contained microarray gene profiling data for 267 patients using 3 different Affymetrix platforms. 191 GBM patients were included in the subsequent data analysis for the Test dataset, all of whom were profiled using the Affymetrix U133A array. The median age of patients in the Test dataset was 54 years (range 18-86 years). 73/191 (38.2%) of patients were female. Patients were followed up for a median of 385 days (range 7-3353 days) and at the end of follow-up 176/191 (92.1%) had died.
3
ANTXR1 Expression Profiling in Human Tissues
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mRNA expression data for ANTXR1 in various human tissues were obtained from the GeneAtlas U133A, gcrma database, which was generated using Affymetrix U133A array to profile gene expression in diverse human tissues.25 (link)
ANTXR1 data from the 220092_s probe set were adapted to create custom graphs. Original data and graphs were available through the BioGPS website (http://biogps.org ).
ANTXR1 data from the 220092_s probe set were adapted to create custom graphs. Original data and graphs were available through the BioGPS website (
4
Microarray Data Normalization and Integration
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We have used previously reported data corresponding to 28 cell lines (GEO: GSE5845) [25 (link)] and have generated expression data for 20 additional cell lines (GSE64279). RNA was isolated with Trizol in both experimental batches. For the new cell lines, RNA (500 ng) was amplified, labeled, and used for array hybridization. The Affymetrix U133A array was used in all experiments. Raw expression data from all experiments were normalized using the R library Frozen Robust Multiarray Analysis (fRMA) method [44 (link)]. We applied this method as described by the authors for multiple arrays. We read the raw data (CEL files) and used the Random effect model for preprocessing. This model allows us combining data from different batches using the same microarray platform for analysis. Further, to obtain a matrix of gene-level expression values we used the exprs function with parameters by default.
5
Prognostic Impact of CYTL1 in Melanoma
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From the GEO database, we chose the profiles GSE46517 and GSE114445. 31 melanoma, nine nevus, and eight normal skin samples were included in GSE46517, which was built on the Agilent GPL96 platform (HG-U133A, Affymetrix Human Genome, U133A Array). The Agilent GPL570 platform-based GSE114445 (HG-U133 Plus 2, Affymetrix Human Genome U133 Plus 2.0 Array) contained 16 melanoma, seven dysplastic nevus samples, and six healthy skin samples. We studied the prognostic impact of CYTL1 in different tumors using the TIMER2.0 database (Li et al., 2020 (link)) and CYTL1 mutations and CNA in melanoma samples from 12 databases using the cBioPortal database (Cerami et al., 2012 (link)).
6
Analyzing mRNA Profiles in cSCC and Skin
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mRNA expression data from the public genome-wide datasets Nindl-15 (Affymetrix U133A array; GSE2503) and Riker-87 (Affymetrix U133P2 array; GSE7553) containing human cSCC and normal skin samples were retrieved from the NCBI Gene Expression Omnibus (GEO) site (http://www.ncbi.nlm.nih.gov/geo/ ). The R2 TranscriptView genomic analysis and visualization tool was used to check if Affymetrix probe-sets had a unique anti-sense position in an exon of the gene. R2 was developed in the Department of Oncogenomics at the Academic Medical Center – University of Amsterdam, the Netherlands and is accessible at http://r2.amc.nl . All probe-sets selected meet these criteria. The probe-set for RasGRP1 (205590_at) is directed against its 3’ UTR and thereby detects both RasGRP1 variants. All expression values and other details for the datasets used can be obtained thru their GSE number on the NCBI GEO website.
7
Transcriptome Analysis of Tubule Samples
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Purified total RNAs from 95 tubule samples were amplified using the Ovation Pico WTA System V2 (NuGEN) and labeled with the Encore Biotin Module (NuGEN) according to the manufacturer's protocol. The purified total RNA from 41 tubule samples used for validation were amplified using the Two-Cycle Target Labeling Kit (Affymetrix) as per the manufacturer's protocol. Transcript levels were analyzed using Affymetrix U133A arrays.
8
Transcriptional Profiling of Diabetic Kidney Disease
9
Transcriptional Profiling of Diabetic Kidney Disease
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Tissue expression of mRNA encoding proteins of interest in the present study was derived from the 1KGP collection19 (link). Tubular (n=37) and glomerular (n=23) mRNA expression was derived from subjects with T2D, various ethnic ancestries and overt DKD (for clinical characteristics and histology indices, please refer to Supplementary Table 5 . Kidney samples were obtained from routine surgical nephrectomies, stored in RNAlater, and manually micro-dissected under a microscope to separate the glomerular and tubular compartments. RNA quality and quantity were determined using the Laboratory-on-Chip Total RNA PicoKit Agilent BioAnalyzer, and only samples without evidence of degradation were used (RNA integrity number>6). Purified total RNAs were amplified using the Ovation Pico WTA System V2 (NuGEN) and labeled with the Encore Biotin Module (NuGEN) according to the manufacturer’s protocol. Transcript levels were analyzed using Affymetrix U133A arrays, and raw expression levels were summarized using the RMA16 algorithm by the justRMA function of the Affy package. Details on clinical characteristics and histology indices are provided in Supplemental Table 5 . Proteinuria was determined with a dipstick score with values from 0 to 5 approximating the following proteinuria ranges: 0-negative, 1 – trace, 2 – 30, 3–100, 4–300, 5>300 mg/100 ml of protein concentration.
10
TCGA TNBC Transcriptomic Analysis
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The R package GSVA95 (link) was used to analyse data from TNBC patients of the TCGA dataset41 (link). In order to enrich for patients with high expression of TIC or EMT gene signatures, ssGSEA was applied using the indicated published gene signatures. Welch two-sample t test was used to compare the expression of single genes, as well as MET and FGFR1 activation signatures between TIC/EMT high and TIC/EMT low patient cohorts.
The gene expression-based outcome for breast cancer online (GOBO) tool (http://co.bmc.lu.se/gobo/ ) was used to determine the association of HGF, FGFR1, EGF and EGFR expression with relapse-free survival across a large set of breast cancers analysed by Affymetrix U133A arrays96 (link).
The gene expression-based outcome for breast cancer online (GOBO) tool (
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