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Title:
Statistical Methods for Identifying Differentially Expressed Genes in DNA Microarrays | SpringerLink
Description:
In this chapter we discuss the problem of identifying differentially expressed genes from a set of microarray experiments. Statistically speaking, this task falls under the heading of “multiple hypothesis testing.” In other words, we must perform...
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Keywords {🔍}

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Topics {✒️}

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Schema {🗺️}

ScholarlyArticle:
      headline:Statistical Methods for Identifying Differentially Expressed Genes in DNA Microarrays
      pageEnd:157
      pageStart:149
      image:https://media.springernature.com/w153/springer-static/cover/book/978-1-59259-364-4.jpg
      genre:
         Springer Protocols
      isPartOf:
         name:Functional Genomics
         isbn:
            978-1-59259-364-4
            978-1-58829-291-9
         type:Book
      publisher:
         name:Humana Press
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:John D. Storey
            affiliation:
                  name:Stanford University
                  address:
                     name:Department of Statistics, Stanford University, Palo Alto
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Robert Tibshirani
            affiliation:
                  name:Stanford University
                  address:
                     name:Department of Statistics, Stanford University, Palo Alto
                     type:PostalAddress
                  type:Organization
                  name:Stanford University
                  address:
                     name:Department of Health Research & Policy, Stanford University, Palo Alto
                     type:PostalAddress
                  type:Organization
            type:Person
      keywords:Rejection Region, Multiple Hypothesis Testing, Null Hypothesis, False Positives, Familywise Error Rate (FWER)
      description:In this chapter we discuss the problem of identifying differentially expressed genes from a set of microarray experiments. Statistically speaking, this task falls under the heading of “multiple hypothesis testing.” In other words, we must perform hypothesis tests on all genes simultaneously to determine whether each one is differentially expressed. Recall that in statistical hypothesis testing, we test a null hypothesis vs an alternative hypothesis. In this example, the null hypothesis is that there is no change in expression levels between experimental conditions. The alternative hypothesis is that there is some change. We reject the null hypothesis if there is enough evidence in favor of the alternative. This amounts to rejecting the null hypothesis if its corresponding statistic falls into some predetermined rejection region. Hypothesis testing is also concerned with measuring the probability of rejecting the null hypothesis when it is really true (called a false positive), and the probability of rejecting the null hypothesis when the alternative hypothesis is really true (called power).
      datePublished:2003
      isAccessibleForFree:
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      context:https://schema.org
Book:
      name:Functional Genomics
      isbn:
         978-1-59259-364-4
         978-1-58829-291-9
Organization:
      name:Humana Press
      logo:
         url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
         type:ImageObject
      name:Stanford University
      address:
         name:Department of Statistics, Stanford University, Palo Alto
         type:PostalAddress
      name:Stanford University
      address:
         name:Department of Statistics, Stanford University, Palo Alto
         type:PostalAddress
      name:Stanford University
      address:
         name:Department of Health Research & Policy, Stanford University, Palo Alto
         type:PostalAddress
ImageObject:
      url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
Person:
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      affiliation:
            name:Stanford University
            address:
               name:Department of Statistics, Stanford University, Palo Alto
               type:PostalAddress
            type:Organization
      name:Robert Tibshirani
      affiliation:
            name:Stanford University
            address:
               name:Department of Statistics, Stanford University, Palo Alto
               type:PostalAddress
            type:Organization
            name:Stanford University
            address:
               name:Department of Health Research & Policy, Stanford University, Palo Alto
               type:PostalAddress
            type:Organization
PostalAddress:
      name:Department of Statistics, Stanford University, Palo Alto
      name:Department of Statistics, Stanford University, Palo Alto
      name:Department of Health Research & Policy, Stanford University, Palo Alto
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