Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data
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Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data. / Aizpurua, Ostaizka; Dunn, Robert R.; Hansen, Lars H.; Gilbert, M. T. P.; Alberdi, Antton.
In: Critical Reviews in Biotechnology, 2024.Research output: Contribution to journal › Review › Research › peer-review
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TY - JOUR
T1 - Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data
AU - Aizpurua, Ostaizka
AU - Dunn, Robert R.
AU - Hansen, Lars H.
AU - Gilbert, M. T. P.
AU - Alberdi, Antton
N1 - Publisher Copyright: © 2023 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2024
Y1 - 2024
N2 - Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results.
AB - Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results.
KW - Batch effect
KW - bias
KW - contamination
KW - controls
KW - extraction
KW - library preparation
KW - metagenome
KW - microbiology
KW - microbiome
KW - study design
U2 - 10.1080/07388551.2023.2254933
DO - 10.1080/07388551.2023.2254933
M3 - Review
C2 - 37731336
AN - SCOPUS:85171643336
JO - Critical Reviews in Biotechnology
JF - Critical Reviews in Biotechnology
SN - 0738-8551
ER -
ID: 368807495