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+
+
+
+ 20231219T121851-95eaa0242185a14cd87829bd8407b132fc0dceba
+ 20231219121851
+
+ JOSS Admin
+ admin@theoj.org
+
+ The Open Journal
+
+
+
+
+ Journal of Open Source Software
+ JOSS
+ 2475-9066
+
+ 10.21105/joss
+ https://joss.theoj.org
+
+
+
+
+ 12
+ 2023
+
+
+ 8
+
+ 92
+
+
+
+ MiscMetabar: an R package to facilitate visualization
+and reproducibility in metabarcoding analysis
+
+
+
+ Adrien
+ Taudière
+ https://orcid.org/0000-0003-1088-1182
+
+
+
+ 12
+ 19
+ 2023
+
+
+ 6038
+
+
+ 10.21105/joss.06038
+
+
+ http://creativecommons.org/licenses/by/4.0/
+ http://creativecommons.org/licenses/by/4.0/
+ http://creativecommons.org/licenses/by/4.0/
+
+
+
+ Software archive
+ 10.5281/zenodo.10370781
+
+
+ GitHub review issue
+ https://github.com/openjournals/joss-reviews/issues/6038
+
+
+
+ 10.21105/joss.06038
+ https://joss.theoj.org/papers/10.21105/joss.06038
+
+
+ https://joss.theoj.org/papers/10.21105/joss.06038.pdf
+
+
+
+
+
+ Basic local alignment search
+tool
+ Altschul
+ Journal of molecular biology
+ 3
+ 215
+ 10.32388/rhq6vj
+ 1990
+ Altschul, S. F., Gish, W., Miller,
+W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment
+search tool. Journal of Molecular Biology, 215(3), 403–410.
+https://doi.org/10.32388/rhq6vj
+
+
+ microViz: An r package for microbiome data
+visualization and statistics
+ Barnett
+ Journal of Open Source
+Software
+ 63
+ 6
+ 10.21105/joss.03201
+ 2021
+ Barnett, D. J. M., Arts, I. C. W.,
+& Penders, J. (2021). microViz: An r package for microbiome data
+visualization and statistics. Journal of Open Source Software, 6(63),
+3201. https://doi.org/10.21105/joss.03201
+
+
+ Reproducible, interactive, scalable and
+extensible microbiome data science using QIIME 2
+ Bolyen
+ Nature biotechnology
+ 8
+ 37
+ 10.1038/s41587-019-0209-9
+ 2019
+ Bolyen, E., Rideout, J. R., Dillon,
+M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A., Alexander, H.,
+Alm, E. J., Arumugam, M., Asnicar, F., & others. (2019).
+Reproducible, interactive, scalable and extensible microbiome data
+science using QIIME 2. Nature Biotechnology, 37(8), 852–857.
+https://doi.org/10.1038/s41587-019-0209-9
+
+
+ Effects of forest urbanization on the
+interplay between small mammal communities and their gut
+microbiota
+ Bouilloud
+ bioRxiv
+ 10.21105/joss.03201
+ 2023
+ Bouilloud, M., Galan, M., Pradel, J.,
+Loiseau, A., FERRERO, J., Gallet, R., Roche, B., & Charbonnel, N.
+(2023). Effects of forest urbanization on the interplay between small
+mammal communities and their gut microbiota. bioRxiv, 2023–2009.
+https://doi.org/10.21105/joss.03201
+
+
+ DADA2: High-resolution sample inference from
+illumina amplicon data
+ Callahan
+ Nature methods
+ 7
+ 13
+ 10.1038/nmeth.3869
+ 2016
+ Callahan, B. J., McMurdie, P. J.,
+Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016).
+DADA2: High-resolution sample inference from illumina amplicon data.
+Nature Methods, 13(7), 581–583.
+https://doi.org/10.1038/nmeth.3869
+
+
+ Mia: Microbiome analysis
+ Ernst
+ 10.18129/B9.bioc.mia
+ 2023
+ Ernst, F. G. M., Shetty, S. A.,
+Borman, T., & Lahti, L. (2023). Mia: Microbiome analysis.
+https://doi.org/10.18129/B9.bioc.mia
+
+
+ Algorithm for post-clustering curation of DNA
+amplicon data yields reliable biodiversity estimates
+ Frøslev
+ Nature communications
+ 1
+ 8
+ 10.1038/s41467-017-01312-x
+ 2017
+ Frøslev, T. G., Kjøller, R., Bruun,
+H. H., Ejrnæs, R., Brunbjerg, A. K., Pietroni, C., & Hansen, A. J.
+(2017). Algorithm for post-clustering curation of DNA amplicon data
+yields reliable biodiversity estimates. Nature Communications, 8(1),
+1188. https://doi.org/10.1038/s41467-017-01312-x
+
+
+ The galaxy platform for accessible,
+reproducible and collaborative biomedical analyses: 2020
+update
+ Jalili
+ Nucleic acids research
+ W1
+ 48
+ 10.1093/nar/gkaa434
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+Clements, D., Blankenberg, D., Goecks, J., Taylor, J., & Nekrutenko,
+A. (2020). The galaxy platform for accessible, reproducible and
+collaborative biomedical analyses: 2020 update. Nucleic Acids Research,
+48(W1), W395–W402.
+https://doi.org/10.1093/nar/gkaa434
+
+
+ The targets r package: A dynamic make-like
+function-oriented pipeline toolkit for reproducibility and
+high-performance computing
+ Landau
+ Journal of Open Source
+Software
+ 57
+ 6
+ 10.21105/joss.02959
+ 2021
+ Landau, W. M. (2021). The targets r
+package: A dynamic make-like function-oriented pipeline toolkit for
+reproducibility and high-performance computing. Journal of Open Source
+Software, 6(57), 2959.
+https://doi.org/10.21105/joss.02959
+
+
+ Mumu: Post-clustering curation tool for
+metabarcoding data
+ Mahé
+ 2023
+ Mahé, F. (2023). Mumu:
+Post-clustering curation tool for metabarcoding data (Version 1.0.2).
+https://github.com/frederic-mahe/mumu/
+
+
+ Meta-analysis of cnidarian microbiomes
+reveals insights into the structure, specificity, and fidelity of marine
+associations.
+ McCauley
+ Research Square
+ 10.21203/rs.3.rs-2011054/v1
+ 2022
+ McCauley, M., Goulet, T., Jackson,
+C., & Loesgen, S. (2022). Meta-analysis of cnidarian microbiomes
+reveals insights into the structure, specificity, and fidelity of marine
+associations. Research Square.
+https://doi.org/10.21203/rs.3.rs-2011054/v1
+
+
+ Systematic review of cnidarian microbiomes
+reveals insights into the structure, specificity, and fidelity of marine
+associations
+ McCauley
+ Nature Communications
+ 1
+ 14
+ 10.21203/rs.3.rs-2011054/v1
+ 2023
+ McCauley, M., Goulet, T., Jackson,
+C., & Loesgen, S. (2023). Systematic review of cnidarian microbiomes
+reveals insights into the structure, specificity, and fidelity of marine
+associations. Nature Communications, 14(1), 4899.
+https://doi.org/10.21203/rs.3.rs-2011054/v1
+
+
+ Mikemc/speedyseq: Speedyseq
+v0.2.0
+ McLaren
+ 10.5281/zenodo.3923184
+ 2020
+ McLaren, M. (2020). Mikemc/speedyseq:
+Speedyseq v0.2.0 (Version v0.2.0). Zenodo.
+https://doi.org/10.5281/zenodo.3923184
+
+
+ Phyloseq: An r package for reproducible
+interactive analysis and graphics of microbiome census
+data
+ McMurdie
+ PLoS ONE
+ 4
+ 8
+ 10.1371/journal.pone.0061217
+ 2013
+ McMurdie, P. J., & Holmes, S.
+(2013). Phyloseq: An r package for reproducible interactive analysis and
+graphics of microbiome census data. PLoS ONE, 8(4), e61217.
+https://doi.org/10.1371/journal.pone.0061217
+
+
+ Interactive metagenomic visualization in a
+web browser
+ Ondov
+ BMC bioinformatics
+ 1
+ 12
+ 10.1186/1471-2105-12-385
+ 2011
+ Ondov, B. D., Bergman, N. H., &
+Phillippy, A. M. (2011). Interactive metagenomic visualization in a web
+browser. BMC Bioinformatics, 12(1), 1–10.
+https://doi.org/10.1186/1471-2105-12-385
+
+
+ Bioinformatics matters: The accuracy of plant
+and soil fungal community data is highly dependent on the metabarcoding
+pipeline
+ Pauvert
+ Fungal Ecology
+ 41
+ 10.1016/j.funeco.2019.03.005
+ 2019
+ Pauvert, C., Buée, M., Laval, V.,
+Edel-Hermann, V., Fauchery, L., Gautier, A., Lesur, I., Vallance, J.,
+& Vacher, C. (2019). Bioinformatics matters: The accuracy of plant
+and soil fungal community data is highly dependent on the metabarcoding
+pipeline. Fungal Ecology, 41, 23–33.
+https://doi.org/10.1016/j.funeco.2019.03.005
+
+
+ A plant-based diet supplemented with hermetia
+illucens alone or in combination with poultry by-product meal: One step
+closer to sustainable aquafeeds for european seabass
+ Pleić
+ Journal of Animal Science and
+Biotechnology
+ 1
+ 13
+ 10.1186/s40104-022-00725-z
+ 2022
+ Pleić, I. L., Bušelić, I., Messina,
+M., Hrabar, J., Žuvić, L., Talijančić, I., Žužul, I., Pavelin, T.,
+Anđelić, I., Pleadin, J., Puizina, J., Grubišić, L., Tibaldi, E., &
+Šegvić-Bubić, T. (2022). A plant-based diet supplemented with hermetia
+illucens alone or in combination with poultry by-product meal: One step
+closer to sustainable aquafeeds for european seabass. Journal of Animal
+Science and Biotechnology, 13(1), 77.
+https://doi.org/10.1186/s40104-022-00725-z
+
+
+ R: A language and environment for statistical
+computing
+ R Core Team
+ 2023
+ R Core Team. (2023). R: A language
+and environment for statistical computing. R Foundation for Statistical
+Computing. https://www.R-project.org/
+
+
+ Reintroducing mothur: 10 years
+later
+ Schloss
+ Applied and environmental
+microbiology
+ 2
+ 86
+ 10.1128/aem.02343-19
+ 2020
+ Schloss, P. D. (2020). Reintroducing
+mothur: 10 years later. Applied and Environmental Microbiology, 86(2),
+e02343–19. https://doi.org/10.1128/aem.02343-19
+
+
+ Phylosmith: An r-package for reproducible and
+efficient microbiome analysis with phyloseq-objects
+ Smith
+ Journal of Open Source
+Software
+ 38
+ 4
+ 10.21105/joss.01442
+ 2019
+ Smith, S. D. (2019). Phylosmith: An
+r-package for reproducible and efficient microbiome analysis with
+phyloseq-objects. Journal of Open Source Software, 4(38), 1442.
+https://doi.org/10.21105/joss.01442
+
+
+ Environmental dna
+ Taberlet
+ Molecular ecology
+ 21
+ 10.1002/(issn)2637-4943
+ 2012
+ Taberlet, P., Coissac, E.,
+Hajibabaei, M., & Rieseberg, L. H. (2012). Environmental dna. In
+Molecular ecology (No. 8; Vol. 21, pp. 1789–1793). Wiley Online Library.
+https://doi.org/10.1002/(issn)2637-4943
+
+
+ Best practices in metabarcoding of fungi:
+From experimental design to results
+ Tedersoo
+ Molecular ecology
+ 10
+ 31
+ 10.22541/au.163430390.04226544/v1
+ 2022
+ Tedersoo, L., Bahram, M., Zinger, L.,
+Nilsson, R. H., Kennedy, P. G., Yang, T., Anslan, S., & Mikryukov,
+V. (2022). Best practices in metabarcoding of fungi: From experimental
+design to results. Molecular Ecology, 31(10), 2769–2795.
+https://doi.org/10.22541/au.163430390.04226544/v1
+
+
+ DNA barcoding for ecologists
+ Valentini
+ Trends in ecology &
+evolution
+ 2
+ 24
+ 10.1016/j.tree.2008.09.011
+ 2009
+ Valentini, A., Pompanon, F., &
+Taberlet, P. (2009). DNA barcoding for ecologists. Trends in Ecology
+& Evolution, 24(2), 110–117.
+https://doi.org/10.1016/j.tree.2008.09.011
+
+
+ Bacterial community patterns in the agaricus
+bisporus cultivation system, from compost raw materials to mushroom
+caps
+ Vieira
+ Microbial Ecology
+ 1
+ 84
+ 10.1007/s00248-021-01833-5
+ 2021
+ Vieira, F. R., & Pecchia, J. A.
+(2021). Bacterial community patterns in the agaricus bisporus
+cultivation system, from compost raw materials to mushroom caps.
+Microbial Ecology, 84(1), 20–32.
+https://doi.org/10.1007/s00248-021-01833-5
+
+
+ Manipulating agaricus bisporus developmental
+patterns by passaging microbial communities in complex
+substrates
+ Vieira
+ Microbiology Spectrum
+ 10.1128/spectrum.01978-23
+ 2023
+ Vieira, F. R., Di Tomassi, I.,
+O’Connor, E., Bull, C. T., Pecchia, J. A., & Hockett, K. L. (2023).
+Manipulating agaricus bisporus developmental patterns by passaging
+microbial communities in complex substrates. Microbiology Spectrum,
+e01978–23.
+https://doi.org/10.1128/spectrum.01978-23
+
+
+ The best practice for microbiome analysis
+using r
+ Wen
+ Protein & Cell
+ 10.1093/procel/pwad024
+ 2023
+ Wen, T., Niu, G., Chen, T., Shen, Q.,
+Yuan, J., & Liu, Y.-X. (2023). The best practice for microbiome
+analysis using r. Protein & Cell, pwad024.
+https://doi.org/10.1093/procel/pwad024
+
+
+ MicrobiotaProcess: A comprehensive r package
+for deep mining microbiome
+ Xu
+ The Innovation
+ 2
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+ 10.1016/j.xinn.2023.100388
+ 2023
+ Xu, S., Zhan, L., Tang, W., Wang, Q.,
+Dai, Z., Zhou, L., Feng, T., Chen, M., Wu, T., Hu, E., & others.
+(2023). MicrobiotaProcess: A comprehensive r package for deep mining
+microbiome. The Innovation, 4(2).
+https://doi.org/10.1016/j.xinn.2023.100388
+
+
+
+
+
+
diff --git a/joss.06038/10.21105.joss.06038.jats b/joss.06038/10.21105.joss.06038.jats
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+++ b/joss.06038/10.21105.joss.06038.jats
@@ -0,0 +1,829 @@
+
+
+
+
+
+
+
+Journal of Open Source Software
+JOSS
+
+2475-9066
+
+Open Journals
+
+
+
+6038
+10.21105/joss.06038
+
+MiscMetabar: an R package to facilitate visualization and
+reproducibility in metabarcoding analysis
+
+
+
+https://orcid.org/0000-0003-1088-1182
+
+Taudière
+Adrien
+
+
+
+
+
+IdEst, Saint-Bonnet-de-Salendrinque, 30460
+France
+
+
+
+
+23
+10
+2023
+
+8
+92
+6038
+
+Authors of papers retain copyright and release the
+work under a Creative Commons Attribution 4.0 International License (CC
+BY 4.0)
+2022
+The article authors
+
+Authors of papers retain copyright and release the work under
+a Creative Commons Attribution 4.0 International License (CC BY
+4.0)
+
+
+
+R
+Bioinformatic
+Metagenomics
+Barcoding
+Reproducibility
+
+
+
+
+
+ Summary
+
Describing communities of living organisms increasingly relies on
+ massive DNA sequencing from environmental samples (e-DNA). The
+ analysis of these large amounts of sequences is well established in
+ the R ecosystem, especially for metabarcoding, i.e. the massive
+ sequencing of one or several given DNA regions, called markers. The
+ MiscMetabar package aims to facilitate the
+ description, transformation,
+ exploration, and reproducibility of
+ metabarcoding analysis. Several tutorials are available
+ online.
+
+
+ Statement of Need
+
Biological studies, especially in ecology, health sciences and
+ taxonomy, need to describe the biological composition of samples.
+ During the last twenty years, the development of (i) high-throughput
+ DNA sequencing, (ii) reference databases and (iii) bioinformatics
+ resources have allowed the description of biological communities
+ through metabarcoding. Metabarcoding involves the sequencing of
+ millions (meta-) of short regions of specific DNA
+ (-barcoding, Valentini et al.
+ (2009))
+ often from environmental samples (eDNA, Taberlet et al.
+ (2012))
+ such as human stomach contents, lake water, soil and air.
+
Several platforms (referenced in Tedersoo et al.
+ (2022))
+ such as QIIME2
+ (Bolyen
+ et al., 2019), mothur
+ (Schloss,
+ 2020), and Galaxy
+ (Jalili
+ et al., 2020) allow complete analysis from raw fastq sequences
+ to statistical analysis and visualization. However, the R ecosystem
+ (R Core
+ Team, 2023), is very rich (fig. 1) and more flexible than these
+ platforms.
+
MiscMetabar aims to facilitate the
+ description, transformation,
+ exploration and reproducibility of
+ metabarcoding analysis using R. The development of
+ MiscMetabar relies heavily on the R packages
+ dada2, phyloseq and
+ targets.
+
+
+ State of the Field in R
+
The metabarcoding ecosystem in the R language is mature,
+ well-constructed, and relies on a very active community in both the
+ bioconductor
+ and
+ cran
+ projects. The
+ bioconductor
+ even creates specific task views in
+ Metagenomics
+ and
+ Microbiome.
+
R package
+ dada2
+ (Callahan
+ et al., 2016) provides a highly cited and recommended
+ clustering method
+ (Pauvert
+ et al., 2019).
+ phyloseq
+ (McMurdie
+ & Holmes, 2013) facilitate metagenomics analysis by
+ providing a way to store data (the phyloseq
+ class) and provides graphical and statistical functions.
+ MiscMetabar is based on the
+ phyloseq class from
+ phyloseq, the most cited package in
+ metagenomics
+ (Wen et
+ al., 2023). For a description and comparison of other
+ integrated packages competing with phyloseq, see Wen et al.
+ (2023). Some
+ packages already extend the phyloseq packages, in particular
+ microbiome
+ package collection
+ (Ernst
+ et al., 2023), the speedyseq package
+ (McLaren,
+ 2020) and the package
+ phylosmith
+ (Smith,
+ 2019).
+
+
Important functions of MiscMetabar with their equivalent
+ when available in other R packages: 1. Mia
+ (Ernst
+ et al., 2023); 2. microViz
+ (Barnett
+ et al., 2021); 3. MicrobiotaProcess
+ (Xu et
+ al., 2023); 4 Phylosmith
+ (Smith,
+ 2019).
+
+
+
MiscMetabar enriches this R ecosystem by
+ providing functions to (i) describe your dataset
+ visually, (ii) transform your data, (iii)
+ explore biological diversity (alpha, beta, and taxonomic
+ diversity), and (iv) simplify reproducibility.
+ MiscMetabar is already used by the scientific
+ community in several teams
+ (Bouilloud
+ et al., 2023;
+ Mark
+ McCauley et al., 2022;
+ M.
+ McCauley et al., 2023;
+ Pleić
+ et al., 2022;
+ Vieira
+ et al., 2023;
+ Vieira
+ & Pecchia, 2021).
+
+
+ Features
+
+ Description
+
A quick graphical representation of the phyloseq object is
+ available using the summary_plot_pq()
+ function (fig. 2A). This plot provides an information-rich
+ structural overview of the phyloseq object. The functions
+ krona() and
+ tax_datatable() describe the taxonomy of
+ organisms using krona interactive pie chart
+ (Ondov
+ et al., 2011) and
+ datatable
+ libraries, respectively.
+
+
+ Transformation
+
+ Post-clustering
+
Several pipelines use at least two step of clustering. The
+ function asv2otu(), using either the
+ DECIPHER::Clusterize() function from R or
+ the
+ vsearch
+ software allow to recluster existing groups such as
+ ASV (stands for Amplicon Sequence
+ Variant) obtained by the
+ dada2::dada() function (see the vignette
+ reclustering).
+ Another transformation method is implemented in
+ lulu_pq(), which uses Frøslev et al.
+ (2017)’s
+ method for post-clustering curation of DNA amplicon data. Note
+ that a fast and robust C++ re-implementation of lulu called
+ mumu
+ (Mahé,
+ 2023) is also available through the function
+ mumu_pq().
+
+
+ Cleaning and filtering
+
The function clean_pq() validates a
+ phyloseq object, mainly by removing empty taxa and samples, and
+ checking for discrepancies between taxa and sample names in
+ different slots.
+
The filter functions subset_samples_pq()
+ and subset_taxa_pq() complement
+ subset_samples() and
+ subset_taxa() from the
+ phyloseq
+ package, allowing the use of a boolean vector to filter samples or
+ taxa from a phyloseq object.
+
I also implement a function to filter taxa based on their blast
+ to a custom database (filter_asv_blast()).
+ This function uses the blastn software
+ (Altschul
+ et al., 1990) to compare ASV sequences to a database and
+ filter out species that are below a given threshold of e-value
+ and/or bit-score.
+
+
+
+ Exploration
+
MiscMetabar provides a large number of
+ facilities to explore the biological diversity in a phyloseq object.
+ In most functions, a parameter enables the effect of the number of
+ reads (sampling depth) to be controlled by rarefaction or other
+ statistical methods, depending on the function. For example, the
+ alpha diversity analysis (function hill_pq())
+ uses the HSD-Tuckey test on a linear model that includes the square
+ roots of the number of reads as the first explanatory variable.
+
To illustrate the effect of sample variables on the taxonomy,
+ MiscMetabar provides the functions
+ treemap_pq(),
+ multitax_bar_pq() (fig. 2D) and
+ heat_tree_pq() (fig. 2E). The effect of an
+ environmental variable (beta-diversity) on a biological organism can
+ be explored by upset plot (pset_pq();
+ fig. 2F), venn diagram (ggvenn_pq();
+ fig. 2G), and circle plot (circle_pq()). This
+ effect can be tested with PERMANOVA
+ (adonis_pq()) and the network test
+ (graph_test_pq()). If only two modalities are
+ compared, biplot_pq() is very useful
+ (fig. 2H). Differential abundance analysis can be performed directly
+ using the plot_deseq2_pq() function
+ (fig. 2I).
+
+
Some illustrations from MiscMetabar with the tengeler
+ dataset from mia R package
+
+
+
+
+ Reproducibility
+
The targets R package
+ (Landau,
+ 2021) improves the efficiency and reproducibility of the
+ pipeline in R. It orchestrates the stage of the pipeline and stores
+ the objects to skip tasks that are already up to date. Given the
+ complexity, runtime, and parameter sensitivity of bioinformatic
+ analysis, the use of targets is particularly relevant for
+ metabarcoding. I developed functions to list fastq files in a
+ directory (list_fastq_files()) and to track
+ the number of sequences, clusters and samples through the pipeline
+ (track_wkflow()) for a variety of objects.
+ Function write_pq() save an object of class
+ phyloseq and read_pq() read a phyloseq object
+ from files.
+
+
+
+ Acknowledgements
+
I thank Will Landau, Paul McMurdie, and Benjamin Callahan for their
+ excellent R packages on which MiscMetabar
+ rests. I also want to acknowledge Franck Richard, Lise Roy, Élisa
+ Taschen and the
+ Mycea
+ team for the discussion and work around metabarcoding.
+
+
+
+
+
+
+
+ AltschulStephen F
+ GishWarren
+ MillerWebb
+ MyersEugene W
+ LipmanDavid J
+
+ Basic local alignment search tool
+
+ Elsevier
+ 1990
+ 215
+ 3
+ 10.32388/rhq6vj
+ 403
+ 410
+
+
+
+
+
+ BarnettDavid J. M.
+ ArtsIlja C. W.
+ PendersJohn
+
+ microViz: An r package for microbiome data visualization and statistics
+
+ The Open Journal
+ 2021
+ 6
+ 63
+ https://doi.org/10.21105/joss.03201
+ 10.21105/joss.03201
+ 3201
+
+
+
+
+
+
+ BolyenEvan
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