crossquery a web tool for easy associative querying of transcriptome datacrossquery web工具简单的转录组数据的关联查询.pdfVIP

CrossQuery: A Web Tool for Easy Associative Querying of Transcriptome Data 1 . 2,3. 1 1 Toni U. Wagner * , Andreas Fischer , Eva C. Thoma , Manfred Schartl ¨ ¨ 1 Physiological Chemistry I, Biocenter, University of Wurzburg, Wurzburg, Germany, 2 Vascular Biology and Tumor Angiogenesis, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany, 3 Vascular Oncology and Metastasis, German Cancer Research Center Heidelberg (DKFZ-ZMBH Alliance), Heidelberg, Germany Abstract Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep- sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Micros