DNA microarrays have considerably helped to improve the understanding of biological

DNA microarrays have considerably helped to improve the understanding of biological processes and diseases. plasma cells and bone marrow plasma cells. Genes overexpressed in each population and the pathways encoded by these genes are provided as well as how the populations cluster together. All the analyses, tables and figures can be easily done and exported using GenomicScape and this B cell to plasma cell atlas is freely available online. Beyond this B cell to plasma cell atlas, the molecular characteristics of any biological process can be easily and freely investigated by uploading the corresponding transcriptome files into GenomicScape. Author Summary The 924641-59-8 use of DNA microarrays has emerged as a powerful tool for biomedical research to understand complex biological processes and diseases, generating large Rabbit Polyclonal to DGKB amounts of publicly available data. Most of these data remain unused by scientific community due to the lack of easy-to-use bioinformatics resources to analyze them. Here we present GenomicScape (www.genomicscape.com), a free online data-mining platform to identify quickly molecular changes during any biological process. As an example, we used GenomicScape to build a comprehensive and accessible molecular atlas of human B cell differentiation, which will be of great interest for immunologists to further understand normal and malignant B cell differentiation. Introduction Genome-wide expression profile analysis with DNA microarrays has emerged as a powerful tool for biomedical research generating a huge amount of publicly available data. Unfortunately, the majority of these data are poorly used due to the lack of easy-to-use and open access bioinformatics tools to extract and visualize the most prominent information. Although statistical programming frameworks like R and Bioconductor projects provide free bioinformatics packages to analyze the data, they are difficult to use for untrained biologists or physicians, which limits the investigation of the large amounts of publicly available data. Based on our long-lasting experience of mining high throughput data to explore the biology of normal and malignant plasma cells [1C5], we have developed the current easy-to-use GenomicScape web tool (www.genomicscape.com), which allows to quickly analyze the molecular changes during a biological process such as cell differentiation or disease progression. As an illustration, we report here, the molecular portrait of human B cell differentiation using GenomicScape. The knowledge of the differentiation of B cells into plasma cells (PCs) has greatly improved, mostly using animal models [6], but this process is less known in humans because of the difficulty to access lymphoid organs and to mimic in vitro this 924641-59-8 in-vivo process involving multistep cell trafficking, cell interactions and activations. In this study, we took advantage of our previous works about germinal center (GC) B cells and plasma cells [3, 5, 7, 8] with the generation of publicly available transcriptome data of human na?ve B cells (NBCs), centroblasts (CBs), centrocytes (CCs), memory B cells (MBCs), preplasmablasts (prePBs), plasmablasts (PBs), early plasma cells (EPCs) and bone marrow plasma cells (BMPCs). We show here how Genomicscape allows easily building an open access Atlas of the gene expression profiles of human na?ve B cells to mature plasma cells, without any knowledge in bioinformatics. Additionally, all of the numbers and analyses from the manuscript could be ready conveniently using GenomicScape. The current evaluation and internet atlas creation could be expanded to any natural procedure provided high throughput microarray data are published into GenomicScape. Outcomes Supervised evaluation from the gene appearance profiling of na?ve B cells, centroblasts, centrocytes, storage B cells, preplasmablasts, plasmablasts, early plasma cells, and older plasma cells Publicly obtainable gene expression data from the 8 B cell to plasma cell populations were GCRMA normalized and grouped within a Individual B cells to plasma cells GCRMA GenomicScape document offered by http://www.genomicscape.com/microarray/browsedata.php?acc=GS-DT-2. Owning a SAM evaluation using GenomicScape SAM device (find S1 Document) and beginning with 10000 exclusive genes with the best regular deviation (SD), 9303 exclusive genes had been differentially expressed between your 8 B cell to plasma cell populations (SAM multiclass 924641-59-8 evaluation, unpaired Wilcoxon figures, fold transformation 2, 300 permutations, FDR = 0%). When different probe pieces interrogated a same gene, the probe established with the best regular deviation (SD) was chosen. The list.