Search results for "Pie chart"

showing 2 items of 2 documents

Recentrifuge: Robust comparative analysis and contamination removal for metagenomics

2017

Metagenomic sequencing is becoming widespread in biomedical and environmental research, and the pace is increasing even more thanks to nanopore sequencing. With a rising number of samples and data per sample, the challenge of efficiently comparing results within a specimen and between specimens arises. Reagents, laboratory, and host related contaminants complicate such analysis. Contamination is particularly critical in low microbial biomass body sites and environments, where it can comprise most of a sample if not all. Recentrifuge implements a robust method for the removal of negative-control and crossover taxa from the rest of samples. With Recentrifuge, researchers can analyze results f…

0301 basic medicineBig DataSource codeComputer scienceBig dataNegative controlcomputer.software_genrelaw.invention0302 clinical medicineDocumentationlawlcsh:QH301-705.5media_commonEcologyMicrobiotaHigh-Throughput Nucleotide SequencingContaminationComputational Theory and MathematicsDNA ContaminationModeling and SimulationData miningAlgorithmsmedia_common.quotation_subjectComputational biologyBiology03 medical and health sciencesCellular and Molecular NeuroscienceGeneticsHumansMolecular BiologyEcology Evolution Behavior and SystematicsInternetWhole Genome Sequencingbusiness.industryPie chartComputational BiologyCorrectionSequence Analysis DNADNA Contamination030104 developmental biologylcsh:Biology (General)MetagenomicsMicrobial TaxonomyMetagenomeNanopore sequencingMetagenomicsbusinesscomputer030217 neurology & neurosurgerySoftwarePLoS computational biology
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Sectors on sectors (SonS): A new hierarchical clustering visualization tool

2011

Clustering techniques have been widely applied to extract information from high-dimensional data structures in the last few years. Graphs are especially relevant for clustering, but many graphs associated with hierarchical clustering do not give any information about the values of the centroids' attributes and the relationships among them. In this paper, we propose a new visualization approach for hierarchical cluster analysis in which the above-mentioned information is available. The method is based on pie charts. The pie charts are divided into several pie segments or sectors corresponding to each cluster. The radius of each pie segment is proportional to the number of patterns included i…

Computer sciencebusiness.industryPie chartcomputer.software_genreSynthetic datalaw.inventionHierarchical clusteringVisualizationSet (abstract data type)Information extractionData visualizationlawData miningbusinessCluster analysiscomputer2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
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