Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

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Human Monocytes to M-CSF differentiated Macrophages


ABSTRACT: This dataset was created to study M-CSF dependent in vitro differentiation of human monocytes to macrophages as a model process to demonstrate that independent component analysis (ICA) is a useful tool to support and extend knowledge-based strategies and to identify complex regulatory networks or novel regulatory candidate genes. Keywords: M-CSF, Monocytes, Macrophages Samples for microarray analysis were isolated from healthy donors and from donors with Niemann-Pick type C disease. Monocytes were differentiated to macrophages for 4 days in the presence of M-CSF (50 ng/ml,R\&D Systems). Differentiation was confirmed by phase contrast microscopy. Total RNA was extracted from the tissue biopsies according to the manufacturerM-BM-4s instructions using the RNeasy Protect Midi Kit (Qiagen). Purity and integrity of the RNA was assessed on the Agilent 2100 bioanalyzer with the RNA 6000 Nano LabChip reagent set (Agilent Technologies, BM-CM-6blingen, Germany). The RNA was quantified spectrophotometrically and then stored at M-bM-^HM-^R80M-BM-0C. Gene expression profiles were determined using Affymetrix HG-U133A and HG-U133plus2.0. Array scanning and expression analysis was performed using Microarray Analysis Suite 5.0 software. Each array was scaled to a target intensity of 100 (scaling to all probesets). *** CEL files not provided for GSM247170 and GSM247407

ORGANISM(S): Homo sapiens

SUBMITTER: Dominik Lutter 

PROVIDER: E-GEOD-9801 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Analyzing M-CSF dependent monocyte/macrophage differentiation: expression modes and meta-modes derived from an independent component analysis.

Lutter Dominik D   Ugocsai Peter P   Grandl Margot M   Orso Evelyn E   Theis Fabian F   Lang Elmar W EW   Schmitz Gerd G  

BMC bioinformatics 20080217


<h4>Background</h4>The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and algorithms are published continuously, mostly conventional methods like hierarchical clustering algorithms or variance analysis tools are used. Here we take a closer look at independent component analysis (ICA) which is already discussed widely as a new analysis approach. However, deep exploration of its applicab  ...[more]

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