Blog
About

  • Record: found
  • Abstract: not found
  • Article: not found

Ectomycorrhizal fungi slow soil carbon cycling

,

Ecology Letters

Wiley-Blackwell

Read this article at

ScienceOpenPublisher
Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Related collections

      Most cited references 59

      • Record: found
      • Abstract: not found
      • Article: not found

      QIIME allows analysis of high-throughput community sequencing data.

        Bookmark
        • Record: found
        • Abstract: found
        • Article: not found

        Search and clustering orders of magnitude faster than BLAST.

         Robert Edgar (2010)
        Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          Simultaneous inference in general parametric models.

          Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
            Bookmark

            Author and article information

            Journal
            Ecology Letters
            Ecol Lett
            Wiley-Blackwell
            1461023X
            August 2016
            August 23 2016
            : 19
            : 8
            : 937-947
            10.1111/ele.12631
            (Editor)
            © 2016

            http://doi.wiley.com/10.1002/tdm_license_1.1

            Product
            Self URI (article page): http://doi.wiley.com/10.1111/ele.12631

            Comments

            Comment on this article