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      The association between gut microbiome and growth in infants with cystic fibrosis

      , , , , , , , , , ,
      Journal of Cystic Fibrosis
      Elsevier BV

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              PICRUSt2 for prediction of metagenome functions

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                Author and article information

                Contributors
                Journal
                Journal of Cystic Fibrosis
                Journal of Cystic Fibrosis
                Elsevier BV
                15691993
                November 2023
                November 2023
                : 22
                : 6
                : 1010-1016
                Article
                10.1016/j.jcf.2023.08.001
                10840679
                37598041
                cadb4996-0f9b-4eaa-940a-ee4f478455c1
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://www.elsevier.com/open-access/userlicense/1.0/

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