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1 Package leukemiaseset August 14, 2018 Type Package Title Leukemia's microarray gene expression data (expressionset). Version Date Author Sara Aibar, Celia Fontanillo and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain. Maintainer Sara Aibar Depends R (>= ), Biobase (>= 2.5.5) Description Expressionset containing gene expresion data from 60 bone marrow samples of patients with one of the four main types of leukemia (ALL, AML, CLL, CML) or non-leukemia. License GPL (>= 2) LazyLoad yes biocviews Tissue, Genome, Homo_sapiens_Data, CancerData, LeukemiaCancerData, MicroarrayData, ChipOnChipData, TissueMicroarrayData, GEO git_url git_branch RELEASE_3_7 git_last_commit 980d0a1 git_last_commit_date Date/Publication R topics documented: leukemiaseset Index 5 1
2 2 leukemiaseset leukemiaseset Leukemia s microarray gene expression data (expressionset). Description ExpressionSet containing gene expresion data from 60 bone marrow samples of patients with one of the four main types of leukemia (ALL, AML, CLL, CML) or no-leukemia controls. Platform: Affymetrix Human Genome U133 Plus 2.0 Annotation: genemapperhgu133plus2 (CDF from GATExplorer) Mapping: Gene Ensembl ID (20172 features) Usage Format Tissue: Bone Marrow Cell type: Mononuclear cells isolated by Ficoll density centrifugation Disease type: 1. Acute Lymphoblastic Leukemia (ALL). Subtype: c-all / pre-b-all without t(9;22) 2. Acute Myeloid Leukemia (AML). Subtype: Normal karyotype 3. Chronic Lymphocytic Leukemia (CLL) 4. Chronic Myeloid Leukemia (CML) 5. Non-leukemia and healthy bone marrow (NoL) All samples were obtained from untreated patients at the time of diagnosis. Preprocessing: The microarrays were normalized with RMA using a redefined probe mapping from Affymetrix probesets to Ensembl genes (Ensembl IDs ENSG). This alternative Chip Definition File (CDF) with complete unambiguous mapping of microarray probes to genes (GeneMapper) is available at GATExplorer ( (Risueno et al. 2010). data(leukemiaseset) ExpressionSet with phenodata: Project: "Mile1" for all samples Tissue: "BoneMarrow" LeukemiaType: Leukemia type acronym: "ALL", "AML", "CLL", "CML" or "NoL" LeukemiaTypeFullName: The full leukemia type name. Subtype: "AML with normal karyotype and other abnormalities", or "c_all/pre_b_all without t(9 22)" if applies
3 leukemiaseset 3 Details Package: leukemiaseset Type: Package Version: 1.0 Date: License: GPL (>=2) LazyLoad: yes Author(s) Source Author: Sara Aibar, Celia Fontanillo and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain. Maintainer: Sara Aibar <saibar@usal.es> This is a subset of the samples collected by the Microarray Innovations in Leukemia (MILE) study (Kohlmann et al. 2008, Haferlach et al. 2010). Full study microarray raw data can be found at the NCBI Gene Expression Omnibus database (GEO, under series accession number GSE The selected samples are labelled keeping their source GEO IDs. References Kohlmann A, Kipps TJ, Rassenti LZ, Downing JR et al. An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase. Br J Haematol (2008) 142(5): PMID: Haferlach T, Kohlmann A, Wieczorek L, Basso G et al. Clinical utility of microarray-based gene expression profiling in the diagnosis and subclassification of leukemia: report from the International Microarray Innovations in Leukemia Study Group. J Clin Oncol (2010) 28(15): PMID: Risueno A, Fontanillo C, Dinger ME, De Las Rivas J. GATExplorer: genomic and transcriptomic explorer; mapping expression probes to gene loci, transcripts, exons and ncrnas. BMC Bioinformatics (2010) 11:221. PMID: See Also This dataset is used in the examples on package genetclassifier. Examples # Load expression set: library(leukemiaseset) data(leukemiaseset) # ExpressionSet overview:
4 4 leukemiaseset leukemiaseset # Phenodata: pdata(leukemiaseset) # Number of samples per class: summary(leukemiaseset$leukemiatype) # For adding a prefix with the disease to the sample name: samplenames(leukemiaseset) <- paste(leukemiaseset$leukemiatype, samplenames(leukemiaseset), sep="_") colnames(exprs(leukemiaseset))
5 Index Topic cancer Topic datasets Topic expression Topic leukemia Topic microarrays ExpressionSet, 2 genetclassifier, 3 leukemiaseset-package (leukemiaseset), 2 RMA, 2 5
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