Literature DB >> 24681718

Reply to: "a fair comparison".

Joseph N Paulson1, Héctor Corrada Bravo2, Mihai Pop2.   

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Year:  2014        PMID： 24681718     DOI： 10.1038/nmeth.2898

Source DB:  PubMed          Journal:  Nat Methods        ISSN： 1548-7091            Impact factor:   28.547


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  2 in total

1.  A fair comparison.

Authors:  Paul I Costea; Georg Zeller; Shinichi Sunagawa; Peer Bork
Journal:  Nat Methods       Date:  2014-04       Impact factor: 28.547

2.  Differential abundance analysis for microbial marker-gene surveys.

Authors:  Joseph N Paulson; O Colin Stine; Héctor Corrada Bravo; Mihai Pop
Journal:  Nat Methods       Date:  2013-09-29       Impact factor: 28.547
  2 in total
  6 in total

1.  LOCOM: A logistic regression model for testing differential abundance in compositional microbiome data with false discovery rate control.

Authors:  Yingtian Hu; Glen A Satten; Yi-Juan Hu
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-22       Impact factor: 12.779

2.  Phylogeny-guided microbiome OTU-specific association test (POST).

Authors:  Caizhi Huang; Benjamin J Callahan; Michael C Wu; Shannon T Holloway; Hayden Brochu; Wenbin Lu; Xinxia Peng; Jung-Ying Tzeng
Journal:  Microbiome       Date:  2022-06-07       Impact factor: 16.837

3.  Associations between microbial communities and key chemical constituents in U.S. domestic moist snuff.

Authors:  Robert E Tyx; Angel J Rivera; Glen A Satten; Lisa M Keong; Peter Kuklenyik; Grace E Lee; Tameka S Lawler; Jacob B Kimbrell; Stephen B Stanfill; Liza Valentin-Blasini; Clifford H Watson
Journal:  PLoS One       Date:  2022-05-04       Impact factor: 3.752

4.  Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies.

Authors:  Jonathan Thorsen; Asker Brejnrod; Martin Mortensen; Morten A Rasmussen; Jakob Stokholm; Waleed Abu Al-Soud; Søren Sørensen; Hans Bisgaard; Johannes Waage
Journal:  Microbiome       Date:  2016-11-25       Impact factor: 14.650

5.  Normalization and microbial differential abundance strategies depend upon data characteristics.

Authors:  Sophie Weiss; Zhenjiang Zech Xu; Shyamal Peddada; Amnon Amir; Kyle Bittinger; Antonio Gonzalez; Catherine Lozupone; Jesse R Zaneveld; Yoshiki Vázquez-Baeza; Amanda Birmingham; Embriette R Hyde; Rob Knight
Journal:  Microbiome       Date:  2017-03-03       Impact factor: 14.650

Review 6.  Analysis of microbial compositions: a review of normalization and differential abundance analysis.

Authors:  Huang Lin; Shyamal Das Peddada
Journal:  NPJ Biofilms Microbiomes       Date:  2020-12-02       Impact factor: 7.290
  6 in total

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