Evidence map›Paper›PMID 31848574›Full record

ReviewBriefings in bioinformatics2021

Current challenges and best-practice protocols for microbiome analysis.

Richa Bharti, Dominik G Grimm

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 291 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
291citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

291 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Guideline
  5. The Human Respiratory Microbiome: Current Understandings and Future Directions.American journal of respiratory cell and molecular biology · 2023
    Pooled it
  6. Pooled it
  7. Consumption of yacon flour and energy-restricted diet increased the relative abundance of intestinal bacteria in obese adults.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2023
    Trial
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Microbiome-guided cancer immunotherapy: immune mechanisms, resistance pathways, and translational opportunities for precision oncology.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  16. Review
  17. Article
  18. Review
  19. Article
  20. Article

231 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Richa BhartiWeihenstephan-Triesdorf University of Applied Sciences and Technical University of Munich, TUM Campus Straubing for Biotechnology and Sustainability, Straubing, Germany.
Dominik G GrimmWeihenstephan-Triesdorf University of Applied Sciences and Technical University of Munich, TUM Campus Straubing for Biotechnology and Sustainability, Straubing, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analyzing the microbiome of diverse species and environments using next-generation sequencing techniques has significantly enhanced our understanding on metabolic, physiological and ecological roles of environmental microorganisms. However, the analysis of the microbiome is affected by experimental conditions (e.g. sequencing errors and genomic repeats) and computationally intensive and cumbersome downstream analysis (e.g. quality control, assembly, binning and statistical analyses). Moreover, the introduction of new sequencing technologies and protocols led to a flood of new methodologies, which also have an immediate effect on the results of the analyses. The aim of this work is to review the most important workflows for 16S rRNA sequencing and shotgun and long-read metagenomics, as well as to provide best-practice protocols on experimental design, sample processing, sequencing, assembly, binning, annotation and visualization. To simplify and standardize the computational analysis, we provide a set of best-practice workflows for 16S rRNA and metagenomic sequencing data (available at https://github.com/grimmlab/MicrobiomeBestPracticeReview).

Indexed as

Practice Guidelines as TopicAnimalsDNA Barcoding, TaxonomicHumansMetagenomicsMicrobiotaRNA, Ribosomal, 16SSequence Analysis, DNARNA, Ribosomal, 16S16S rRNA sequencingamplicon sequencingassemblyfunctional and taxonomic classificationmetagenomicsmicrobiome

Identifiers

PMID31848574
PMCPMC7820839

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.