Dataset Information

Qiita: rapid, web-enabled microbiome meta-analysis.

ABSTRACT: Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

SUBMITTER: Gonzalez A

PROVIDER: S-EPMC6235622 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Qiita: rapid, web-enabled microbiome meta-analysis.

Gonzalez Antonio A Navas-Molina Jose A JA Kosciolek Tomasz T McDonald Daniel D Vázquez-Baeza Yoshiki Y Ackermann Gail G DeReus Jeff J Janssen Stefan S Swafford Austin D AD Orchanian Stephanie B SB Sanders Jon G JG Shorenstein Joshua J Holste Hannes H Petrus Semar S Robbins-Pianka Adam A Brislawn Colin J CJ Wang Mingxun M Rideout Jai Ram JR Bolyen Evan E Dillon Matthew M Caporaso J Gregory JG Dorrestein Pieter C PC Knight Rob R

Nature methods 20181001 10

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project ...[more]

PMID: 30275573

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Project description:BackgroundWeb-based interventions have been introduced as novel and effective treatments for mental disorders and, in recent years, specifically for the bereaved. However, a systematic summary of the effectiveness of online interventions for people experiencing bereavement is still missing.ObjectiveA systematic literature search was conducted by four reviewers who reviewed and meta-analytically summarized the evidence for web-based interventions for bereaved people.MethodsSystematic searches (PubMed, Web of Science, PsycInfo, PsycArticles, Medline, and CINAHL) resulted in seven randomized controlled trials (N = 1,257) that addressed adults having experienced bereavement using internet-based interventions. We used random effects models to summarize treatment effects for between-group comparisons (treatment vs. control at post) and stability over time (post vs. follow-up).ResultsAll web-based interventions were based on cognitive behavioral therapy (CBT). In comparison with control groups, the interventions showed moderate (g = .54) to large effects (g = .86) for symptoms of grief and posttraumatic stress disorder (PTSD), respectively. The effect for depression was small (g = .44). All effects were stable over time. A higher number of treatment sessions achieved higher effects for grief symptoms and more individual feedback increased effects for depression. Other moderators (i.e. dropout rate, time since loss, exposure) did not significantly reduce moderate degrees of heterogeneity between the studies.LimitationsThe number of includable studies was low in this review resulting to lower power for moderator analyses in particular.ConclusionsOverall, the results of web-based bereavement interventions are promising, and its low-threshold approach might reduce barriers to bereavement care. Nonetheless, future research should further examine potential moderators and specific treatment components (e.g. exposure, feedback) and compare interventions with active controls.

Dataset Information

Qiita: rapid, web-enabled microbiome meta-analysis.

Publications

Qiita: rapid, web-enabled microbiome meta-analysis.

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