We are analyzing https://link.springer.com/article/10.1186/s13059-016-0947-7.

Title:
Pooling across cells to normalize single-cell RNA sequencing data with many zero counts | Genome Biology
Description:
Normalization of single-cell RNA sequencing data is necessary to eliminate cell-specific biases prior to downstream analyses. However, this is not straightforward for noisy single-cell data where many counts are zero. We present a novel approach where expression values are summed across pools of cells, and the summed values are used for normalization. Pool-based size factors are then deconvolved to yield cell-based factors. Our deconvolution approach outperforms existing methods for accurate normalization of cell-specific biases in simulated data. Similar behavior is observed in real data, where deconvolution improves the relevance of results of downstream analyses.
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {📚}

Science
Education
Technology & Computing

Content Management System {📝}

What CMS is link.springer.com built with?

Custom-built

No common CMS systems were detected on Link.springer.com, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of link.springer.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month

Based on our best estimate, this website will receive around 5,000,019 visitors per month in the current month.
However, some sources were not loaded, we suggest to reload the page to get complete results.

check SE Ranking
check Ahrefs
check Similarweb
check Ubersuggest
check Semrush

How Does Link.springer.com Make Money? {💸}

We see no obvious way the site makes money.

Some websites aren't about earning revenue; they're built to connect communities or raise awareness. There are numerous motivations behind creating websites. This might be one of them. Link.springer.com might be making money, but it's not detectable how they're doing it.

Keywords {🔍}

cells, size, genes, data, normalization, library, cell, deconvolution, set, counts, methods, expression, values, factors, factor, zeroes, article, method, gene, additional, estimates, number, pubmed, file, singlecell, existing, deseq, pool, google, scholar, approach, tmm, theta, analysis, stochastic, linear, system, mathcal, sets, differences, large, small, similar, real, rnaseq, unique, cas, sequencing, prior, results,

Topics {✒️}

org/packages/release/bioc/html/topgo org/web/packages/limsolve/citation quantitative single-cell rna-seq single-cell rna-seq experiments org/web/packages/limsolve/index single-cell transcriptomics reveals high-throughput scrna-seq data complex rna-seq experiments multifactor rna-seq experiments single-cell rna-seq single cell rna-sequencing article download pdf single-cell sequencing experiments bulk rna-seq data normalizing rna-seq data simulating scrna-seq data noisy single-cell data cluster-specific reference pseudo-cell single-cell transcriptomics applied supplementary figures s1–s7 scrna-seq data based rank correlation-based distances cancer research uk z_{ij} = y_{ij}t_{ real scrna-seq data real scrna-seq data” normalizing single-cell data simulated scrna-seq data related subjects single-cell transcriptomics single baseline pseudo-cell bulk rna sequencing cluster-specific size factor rna-seq data scrna-seq experiments cluster-specific size factors full size image represent low-quality libraries privacy choices/manage cookies yield cell-based factors kolodziejczyk aa pool-based size factor scrna-seq literature [12–17] pool-based size factors scrna-seq data wellcome genome campus gene-specific nb dispersion averaged reference pseudo-cell gene-specific constant sampled creative commons license

Schema {🗺️}

WebPage:
      mainEntity:
         headline:Pooling across cells to normalize single-cell RNA sequencing data with many zero counts
         description:Normalization of single-cell RNA sequencing data is necessary to eliminate cell-specific biases prior to downstream analyses. However, this is not straightforward for noisy single-cell data where many counts are zero. We present a novel approach where expression values are summed across pools of cells, and the summed values are used for normalization. Pool-based size factors are then deconvolved to yield cell-based factors. Our deconvolution approach outperforms existing methods for accurate normalization of cell-specific biases in simulated data. Similar behavior is observed in real data, where deconvolution improves the relevance of results of downstream analyses.
         datePublished:2016-04-27T00:00:00Z
         dateModified:2016-04-27T00:00:00Z
         pageStart:1
         pageEnd:14
         license:http://creativecommons.org/publicdomain/zero/1.0/
         sameAs:https://doi.org/10.1186/s13059-016-0947-7
         keywords:
            Single-cell RNA-seq
            Normalization
            Differential expression
            Animal Genetics and Genomics
            Human Genetics
            Plant Genetics and Genomics
            Microbial Genetics and Genomics
            Bioinformatics
            Evolutionary Biology
         image:
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig1_HTML.gif
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig2_HTML.gif
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig4_HTML.gif
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig5_HTML.gif
         isPartOf:
            name:Genome Biology
            issn:
               1474-760X
            volumeNumber:17
            type:
               Periodical
               PublicationVolume
         publisher:
            name:BioMed Central
            logo:
               url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
               type:ImageObject
            type:Organization
         author:
               name:Aaron T. L. Lun
               affiliation:
                     name:University of Cambridge
                     address:
                        name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
                        type:PostalAddress
                     type:Organization
               email:[email protected]
               type:Person
               name:Karsten Bach
               affiliation:
                     name:Wellcome Genome Campus
                     address:
                        name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
                        type:PostalAddress
                     type:Organization
               type:Person
               name:John C. Marioni
               affiliation:
                     name:University of Cambridge
                     address:
                        name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
                        type:PostalAddress
                     type:Organization
                     name:Wellcome Genome Campus
                     address:
                        name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
                        type:PostalAddress
                     type:Organization
                     name:Wellcome Genome Campus
                     address:
                        name:Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK
                        type:PostalAddress
                     type:Organization
               email:[email protected]
               type:Person
         isAccessibleForFree:1
         type:ScholarlyArticle
      context:https://schema.org
ScholarlyArticle:
      headline:Pooling across cells to normalize single-cell RNA sequencing data with many zero counts
      description:Normalization of single-cell RNA sequencing data is necessary to eliminate cell-specific biases prior to downstream analyses. However, this is not straightforward for noisy single-cell data where many counts are zero. We present a novel approach where expression values are summed across pools of cells, and the summed values are used for normalization. Pool-based size factors are then deconvolved to yield cell-based factors. Our deconvolution approach outperforms existing methods for accurate normalization of cell-specific biases in simulated data. Similar behavior is observed in real data, where deconvolution improves the relevance of results of downstream analyses.
      datePublished:2016-04-27T00:00:00Z
      dateModified:2016-04-27T00:00:00Z
      pageStart:1
      pageEnd:14
      license:http://creativecommons.org/publicdomain/zero/1.0/
      sameAs:https://doi.org/10.1186/s13059-016-0947-7
      keywords:
         Single-cell RNA-seq
         Normalization
         Differential expression
         Animal Genetics and Genomics
         Human Genetics
         Plant Genetics and Genomics
         Microbial Genetics and Genomics
         Bioinformatics
         Evolutionary Biology
      image:
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig1_HTML.gif
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig2_HTML.gif
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig4_HTML.gif
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1186%2Fs13059-016-0947-7/MediaObjects/13059_2016_947_Fig5_HTML.gif
      isPartOf:
         name:Genome Biology
         issn:
            1474-760X
         volumeNumber:17
         type:
            Periodical
            PublicationVolume
      publisher:
         name:BioMed Central
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:Aaron T. L. Lun
            affiliation:
                  name:University of Cambridge
                  address:
                     name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
            name:Karsten Bach
            affiliation:
                  name:Wellcome Genome Campus
                  address:
                     name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
                     type:PostalAddress
                  type:Organization
            type:Person
            name:John C. Marioni
            affiliation:
                  name:University of Cambridge
                  address:
                     name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
                     type:PostalAddress
                  type:Organization
                  name:Wellcome Genome Campus
                  address:
                     name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
                     type:PostalAddress
                  type:Organization
                  name:Wellcome Genome Campus
                  address:
                     name:Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
      isAccessibleForFree:1
["Periodical","PublicationVolume"]:
      name:Genome Biology
      issn:
         1474-760X
      volumeNumber:17
Organization:
      name:BioMed Central
      logo:
         url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
         type:ImageObject
      name:University of Cambridge
      address:
         name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
         type:PostalAddress
      name:Wellcome Genome Campus
      address:
         name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
         type:PostalAddress
      name:University of Cambridge
      address:
         name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
         type:PostalAddress
      name:Wellcome Genome Campus
      address:
         name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
         type:PostalAddress
      name:Wellcome Genome Campus
      address:
         name:Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK
         type:PostalAddress
ImageObject:
      url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
Person:
      name:Aaron T. L. Lun
      affiliation:
            name:University of Cambridge
            address:
               name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
               type:PostalAddress
            type:Organization
      email:[email protected]
      name:Karsten Bach
      affiliation:
            name:Wellcome Genome Campus
            address:
               name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
               type:PostalAddress
            type:Organization
      name:John C. Marioni
      affiliation:
            name:University of Cambridge
            address:
               name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
               type:PostalAddress
            type:Organization
            name:Wellcome Genome Campus
            address:
               name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
               type:PostalAddress
            type:Organization
            name:Wellcome Genome Campus
            address:
               name:Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
      name:Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
      name:Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK

External Links {🔗}(110)

Analytics and Tracking {📊}

Google Tag Manager

Libraries {📚}

Clipboard.js
Prism.js

CDN Services {📦}

Crossref

4.48s.

LINK . SPRINGER . COM {}