NATURE . COM {}

Analyzed Page
Matching Content Categories
CMS
Monthly Traffic Estimate
How Does Nature.com Make Money
How Much Does Nature.com Make
Keywords
Topics
Questions
Schema
Social Networks
External Links
Analytics And Tracking
Libraries
Hosting Providers
CDN Services

We are analyzing https://www.nature.com/articles/6800717.

Title:
Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix | Heredity
Description:
Correlated multiple testing is widely performed in genetic research, particularly in multilocus analyses of complex diseases. Failure to control appropriately for the effect of multiple testing will either result in a flood of false-positive claims or in true hits being overlooked. Cheverud proposed the idea of adjusting correlated tests as if they were independent, according to an ‘effective number’ (Meff) of independent tests. However, our experience has indicated that Cheverud
Website Age:
30 years and 10 months (reg. 1994-08-11).

Matching Content Categories {📚}

Education
Technology & Computing
Science

Content Management System {📝}

What CMS is nature.com built with?

Custom-built

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

Traffic Estimate {📈}

What is the average monthly size of nature.com audience?

🌆 Monumental Traffic: 20M - 50M visitors per month

Based on our best estimate, this website will receive around 42,554,915 visitors per month in the current month.

check SE Ranking
check Ahrefs
check Similarweb
check Ubersuggest
check Semrush

How Does Nature.com Make Money? {💸}

Display Ads {🎯}

The website utilizes display ads within its content to generate revenue. Check the next section for further revenue estimates.

Ads are managed by yourbow.com. Particular relationships are as follows:

Direct Advertisers (10)

google.com, pmc.com, doceree.com, yourbow.com, audienciad.com, onlinemediasolutions.com, advibe.media, aps.amazon.com, getmediamx.com, onomagic.com

Reseller Advertisers (38)

conversantmedia.com, rubiconproject.com, pubmatic.com, appnexus.com, openx.com, smartadserver.com, lijit.com, sharethrough.com, video.unrulymedia.com, google.com, yahoo.com, triplelift.com, onetag.com, sonobi.com, contextweb.com, 33across.com, indexexchange.com, media.net, themediagrid.com, adform.com, richaudience.com, sovrn.com, improvedigital.com, freewheel.tv, smaato.com, yieldmo.com, amxrtb.com, adyoulike.com, adpone.com, criteo.com, smilewanted.com, 152media.info, e-planning.net, smartyads.com, loopme.com, opera.com, mediafuse.com, betweendigital.com

How Much Does Nature.com Make? {💰}

Display Ads {🎯}

$536,300 per month
Our estimates place Nature.com's monthly online earnings from display ads at $357,503 to $983,134.

Keywords {🔍}

meff, tests, equation, article, analyses, data, google, scholar, pubmed, test, multilocus, fdr, correlated, independent, correlation, method, control, cas, multiple, number, testing, loci, procedure, nature, permutation, ewsl, cheverud, estimate, rate, snps, hypotheses, table, genetic, proposed, methods, rejected, singlelocus, benjamini, applied, genet, eigenvalues, discovery, equal, stepup, study, eigenvalue, central, analysis, false, step,

Topics {✒️}

nature portfolio permissions reprints privacy policy [18f]fe-pe2i dat correlates genetic research experiment-wise significant level nature point-wise significant level advertising social media author information authors fractionation/mass spectrometry platform published schizophrenia data author correspondence multifactor dimensionality reduction mathematical multi-locus approaches suggested resampling-based methods false discovery rate dual-task test verbal angiotensin-i-converting enzyme false discovery rates employed resampling-based methods data-driven algorithm based detecting gene-gene interactions permissions generous sharing china genome-wise type design meff-based procedures quantitative trait mapping simulated case–control data adjusting multiple testing data-driven meff method false-positive claims correlated multiple testing environmental risk factors privacy resampling-based methods single-locus analysis keavney data set explore content similar content k-locus analysis performance single-locus analyses journals search log low replication rate computing approximate thresholds composite interval mapping schizophrenia data set nonintegral part represents

Questions {❓}

Are Genetic and Environmental Risk Factors for Psychopathology Amplified in Children with Below-Average Intelligence?
‘Are we there yet’?

Schema {🗺️}

WebPage:
      mainEntity:
         headline:Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix
         description:Correlated multiple testing is widely performed in genetic research, particularly in multilocus analyses of complex diseases. Failure to control appropriately for the effect of multiple testing will either result in a flood of false-positive claims or in true hits being overlooked. Cheverud proposed the idea of adjusting correlated tests as if they were independent, according to an âeffective numberâ (Meff) of independent tests. However, our experience has indicated that Cheverud's estimate of the Meff is overly large and will lead to excessively conservative results. We propose a more accurate estimate of the Meff, and design Meff-based procedures to control the experiment-wise significant level and the false discovery rate. In an evaluation, based on both real and simulated data, the Meff-based procedures were able to control the error rate accurately and consequently resulted in a power increase, especially in multilocus analyses. The results confirm that the Meff is a useful concept in the error-rate control of correlated tests. With its efficiency and accuracy, the Meff method provides an alternative to computationally intensive methods such as the permutation test.
         datePublished:2005-08-03T00:00:00Z
         dateModified:2005-08-03T00:00:00Z
         pageStart:221
         pageEnd:227
         sameAs:https://doi.org/10.1038/sj.hdy.6800717
         keywords:
            multilocus analysis
            multiple testing
            experiment-wise significant level
            false discovery rate
            Biomedicine
            general
            Human Genetics
            Evolutionary Biology
            Ecology
            Cytogenetics
            Plant Genetics and Genomics
         image:
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1038%2Fsj.hdy.6800717/MediaObjects/41437_2005_Article_BF6800717_Fig1_HTML.gif
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1038%2Fsj.hdy.6800717/MediaObjects/41437_2005_Article_BF6800717_Fig2_HTML.gif
         isPartOf:
            name:Heredity
            issn:
               1365-2540
               0018-067X
            volumeNumber:95
            type:
               Periodical
               PublicationVolume
         publisher:
            name:Springer International Publishing
            logo:
               url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
               type:ImageObject
            type:Organization
         author:
               name:J Li
               affiliation:
                     name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
                     address:
                        name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
                        type:PostalAddress
                     type:Organization
               type:Person
               name:L Ji
               affiliation:
                     name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
                     address:
                        name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
                        type:PostalAddress
                     type:Organization
               email:[email protected]
               type:Person
         isAccessibleForFree:1
         type:ScholarlyArticle
      context:https://schema.org
ScholarlyArticle:
      headline:Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix
      description:Correlated multiple testing is widely performed in genetic research, particularly in multilocus analyses of complex diseases. Failure to control appropriately for the effect of multiple testing will either result in a flood of false-positive claims or in true hits being overlooked. Cheverud proposed the idea of adjusting correlated tests as if they were independent, according to an âeffective numberâ (Meff) of independent tests. However, our experience has indicated that Cheverud's estimate of the Meff is overly large and will lead to excessively conservative results. We propose a more accurate estimate of the Meff, and design Meff-based procedures to control the experiment-wise significant level and the false discovery rate. In an evaluation, based on both real and simulated data, the Meff-based procedures were able to control the error rate accurately and consequently resulted in a power increase, especially in multilocus analyses. The results confirm that the Meff is a useful concept in the error-rate control of correlated tests. With its efficiency and accuracy, the Meff method provides an alternative to computationally intensive methods such as the permutation test.
      datePublished:2005-08-03T00:00:00Z
      dateModified:2005-08-03T00:00:00Z
      pageStart:221
      pageEnd:227
      sameAs:https://doi.org/10.1038/sj.hdy.6800717
      keywords:
         multilocus analysis
         multiple testing
         experiment-wise significant level
         false discovery rate
         Biomedicine
         general
         Human Genetics
         Evolutionary Biology
         Ecology
         Cytogenetics
         Plant Genetics and Genomics
      image:
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1038%2Fsj.hdy.6800717/MediaObjects/41437_2005_Article_BF6800717_Fig1_HTML.gif
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1038%2Fsj.hdy.6800717/MediaObjects/41437_2005_Article_BF6800717_Fig2_HTML.gif
      isPartOf:
         name:Heredity
         issn:
            1365-2540
            0018-067X
         volumeNumber:95
         type:
            Periodical
            PublicationVolume
      publisher:
         name:Springer International Publishing
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:J Li
            affiliation:
                  name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
                  address:
                     name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
                     type:PostalAddress
                  type:Organization
            type:Person
            name:L Ji
            affiliation:
                  name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
                  address:
                     name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
      isAccessibleForFree:1
["Periodical","PublicationVolume"]:
      name:Heredity
      issn:
         1365-2540
         0018-067X
      volumeNumber:95
Organization:
      name:Springer International Publishing
      logo:
         url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
         type:ImageObject
      name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
      address:
         name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
         type:PostalAddress
      name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
      address:
         name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
         type:PostalAddress
ImageObject:
      url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
Person:
      name:J Li
      affiliation:
            name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
            address:
               name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
               type:PostalAddress
            type:Organization
      name:L Ji
      affiliation:
            name:The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University
            address:
               name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China
      name:Department of Automation, The Ministry of Education (MOE) Key Laboratory of Bioinformatics, Tsinghua University, Beijing, People's Republic of China

Social Networks {👍}(1)

https://twitter.com/HeredityJournal

External Links {🔗}(95)

Analytics and Tracking {📊}

Google Tag Manager

Libraries {📚}

Prism.js
Zoom.js

Emails and Hosting {✉️}

Mail Servers:

mxa-002c5801.gslb.pphosted.com
mxb-002c5801.gslb.pphosted.com

Name Servers:

pdns1.ultradns.net
pdns2.ultradns.net
pdns3.ultradns.org
pdns4.ultradns.org
pdns5.ultradns.info
pdns6.ultradns.co.uk

CDN Services {📦}

Crossref

4.16s.