We are analyzing https://link.springer.com/article/10.1186/s13059-017-1382-0.

Title:
SCANPY: large-scale single-cell gene expression data analysis | Genome Biology
Description:
Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells ( https://github.com/theislab/Scanpy ). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices ( https://github.com/theislab/anndata ).
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Keywords {🔍}

data, article, pubmed, google, scholar, singlecell, analysis, cells, scanpy, cell, expression, central, python, cas, clustering, nat, gene, anndata, scanpys, diffusion, open, methods, access, package, research, software, theis, visualization, class, tool, learning, tools, genome, scalable, sets, million, simple, ranger, maps, fig, single, graph, biotechnol, authors, privacy, cookies, content, largescale, wolf, angerer,

Topics {✒️}

high-dimensional single-cell analysis high-dimensional single-cell data /theislab/scanpy_usage/tree/master/170505_seurat /theislab/scanpy_usage/tree/master/170503_zheng17 /theislab/scanpy_usage/tree/master/170522_visualizing_one_million_cells /theislab/scanpy_usage/tree/master/170502_haghverdi16 /theislab/scanpy_usage/tree/master/170430_krumsiek11 /theislab/scanpy_usage/tree/master/170529_images large-scale single-cell data single-cell rna-seq data compute random-walk-based metrics differential expression testing large-scale machine learning single-cell rna-seq tree-inference tool eclair advanced machine-learning packages scalability directly addresses gene expression data single-cell analysis toolkit differential expression tests t-cell receptor signaling exploit online-learning formulations article download pdf complex network research data-driven phenotypic dissection single-cell analysis trajectory inference large-scale data gene regulatory networks existing r-based frameworks established r-based frameworks simplify memory-efficient pipelines 3-million-cell data set analyzing deep-learning results german research foundation low-dimensional analysis single-cell data single-cell clustering pseudotemporal ordering single graph representation single-cell images [25] single-cell genomics single-cell transcriptomes privacy choices/manage cookies open source software ms4a1 marker gene related subjects transcriptomics open-source code org/proceedings/scipy2010/mckinney

Schema {🗺️}

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         headline:SCANPY: large-scale single-cell gene expression data analysis
         description:Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells ( https://github.com/theislab/Scanpy ). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices ( https://github.com/theislab/anndata ).
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         dateModified:2018-02-06T00:00:00Z
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            Single-cell transcriptomics
            Machine learning
            Scalability
            Graph analysis
            Clustering
            Pseudotemporal ordering
            Trajectory inference
            Differential expression testing
            Visualization
            Bioinformatics
            Animal Genetics and Genomics
            Human Genetics
            Plant Genetics and Genomics
            Microbial Genetics and Genomics
            Evolutionary Biology
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      headline:SCANPY: large-scale single-cell gene expression data analysis
      description:Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells ( https://github.com/theislab/Scanpy ). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices ( https://github.com/theislab/anndata ).
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      dateModified:2018-02-06T00:00:00Z
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         Single-cell transcriptomics
         Machine learning
         Scalability
         Graph analysis
         Clustering
         Pseudotemporal ordering
         Trajectory inference
         Differential expression testing
         Visualization
         Bioinformatics
         Animal Genetics and Genomics
         Human Genetics
         Plant Genetics and Genomics
         Microbial Genetics and Genomics
         Evolutionary Biology
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            type:Person
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                  address:
                     name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Fabian J. Theis
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                  address:
                     name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
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         name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
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            name:Institute of Computational Biology
            address:
               name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
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      email:[email protected]
      name:Philipp Angerer
      affiliation:
            name:Institute of Computational Biology
            address:
               name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
               type:PostalAddress
            type:Organization
      name:Fabian J. Theis
      affiliation:
            name:Institute of Computational Biology
            address:
               name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
               type:PostalAddress
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            name:Technische Universität München
            address:
               name:Department of Mathematics, Technische Universität München, Munich, Germany
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      name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
      name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
      name:Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology, Munich, Germany
      name:Department of Mathematics, Technische Universität München, Munich, Germany

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