N. Qin, F. Yang, A. Li, E. Prifti, Y. Chen et al., Alterations of the human gut microbiome in liver cirrhosis, Nature, vol.513, pp.59-64, 2014.
URL : https://hal.archives-ouvertes.fr/hal-02639870

M. Pop, A. W. Walker, J. Paulson, B. Lindsay, M. Antonio et al., Diarrhea in young children from low-income countries leads to large-scale alterations in intestinal microbiota composition, Genome Biol, vol.15, issue.6, pp.1-12, 2014.

G. Zeller, J. Tap, A. Y. Voigt, S. Sunagawa, J. R. Kultima et al., Potential of fecal microbiota for early-stage detection of colorectal cancer, Mol Syst Biol, vol.10, p.766, 2014.

J. J. Quereda, O. Dussurget, M. Nahori, A. Ghozlane, S. Volant et al., Proc Natl Acad Sci U S A, vol.113, pp.5706-5717, 2016.

P. Veiga, C. A. Gallini, C. Beal, M. Michaud, M. L. Delaney et al., Bifidobacterium animalis subsp. lactis fermented milk product reduces inflammation by altering a niche for colitogenic microbes, Proc Natl Acad Sci, vol.107, issue.42, pp.18132-18139, 2010.

S. L. Westcott and P. D. Schloss, De novo clustering methods outperform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units, PeerJ, vol.3, p.1487, 2015.

P. D. Schloss, S. L. Westcott, T. Ryabin, J. R. Hall, M. Hartmann et al., Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities, Appl Environ Microbiol, vol.75, pp.7537-7578, 2009.

R. C. Edgar, UPARSE: highly accurate OTU sequences from microbial amplicon reads, Nat Methods, vol.10, pp.996-1004, 2013.

B. J. Callahan, P. J. Mcmurdie, M. J. Rosen, A. W. Han, A. Johnson et al., DADA2: high-resolution sample inference from Illumina amplicon data, Nat Methods, vol.13, pp.581-584, 2016.

T. Rognes, T. Flouri, B. Nichols, C. Quince, and F. Mahé, VSEARCH: a versatile open source tool for metagenomics, PeerJ, vol.4, p.2584, 2016.

J. G. Caporaso, J. Kuczynski, J. Stombaugh, K. Bittinger, F. D. Bushman et al., QIIME allows analysis of high-throughput community sequencing data, Nat Methods, vol.7, issue.5, pp.335-341, 2010.

D. Mcdonald, J. C. Clemente, J. Kuczynski, J. R. Rideout, J. Stombaugh et al., The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome, GigaScience, vol.1, issue.1, pp.2047-2064, 2012.

J. N. Paulson, M. Pop, and H. C. Bravo, Metastats: an improved statistical method for analysis of metagenomic data, Genome Biol, vol.12, issue.1, pp.1-27, 2011.

J. N. Paulson, O. C. Stine, H. C. Bravo, and M. Pop, Differential abundance analysis for microbial marker-gene surveys, Nat Methods, vol.10, pp.1200-1202, 2013.

M. I. Love, W. Huber, and S. Anders, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2, Genome Biol, vol.15, p.550, 2014.

M. D. Robinson, D. J. Mccarthy, and G. K. Smyth, edgeR: a Bioconductor package for differential expression analysis of digital gene expression data, Bioinformatics, vol.26, issue.1, pp.139-179, 2010.

P. J. Mcmurdie and S. Holmes, Waste not, want not: why rarefying microbiome data is inadmissible, PLoS Comput Biol, vol.10, issue.4, p.1003531, 2014.

V. Jonsson, T. Österlund, O. Nerman, and E. Kristiansson, Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics, BMC Genomics, vol.17, issue.1, p.78, 2016.

F. Escudié, L. Auer, M. Bernard, M. Mariadassou, L. Cauquil et al., FROGS: find, rapidly, OTUs with galaxy solution, Bioinformatics, vol.34, issue.8, pp.1287-94, 2017.

B. Batut, K. Gravouil, C. Defois, S. Hiltemann, J. Brugère et al., ASaiM: a Galaxy-based framework to analyze microbiota data. GigaScience, vol.7, p.57, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01990448

A. Gonzalez, J. A. Navas-molina, T. Kosciolek, D. Mcdonald, Y. Vázquez-baeza et al., Qiita: rapid, web-enabled microbiome meta-analysis, Nat Methods, vol.15, pp.796-804, 2018.

M. W. Thang, X. Chua, G. Price, D. Gorse, and M. A. Field, MetaDEGalaxy: Galaxy workflow for differential abundance analysis of 16s metagenomic data, vol.8, 2019.

P. J. Mcmurdie and S. Holmes, Shiny-phyloseq: Web application for interactive microbiome analysis with provenance tracking, Bioinformatics, vol.31, pp.282-285, 2015.

J. Wagner, F. Chelaru, J. Kancherla, J. N. Paulson, A. Zhang et al., Metaviz: interactive statistical and visual analysis of metagenomic data, Nucleic Acids Res, vol.46, issue.6, pp.2777-87, 2018.

S. M. Huse, M. Welch, D. B. Voorhis, A. Shipunova, A. Morrison et al., VAMPS: a website for visualization and analysis of microbial population structures, BMC Bioinformatics, vol.15, p.41, 2014.

E. Afgan, D. Baker, B. Batut, M. Van-den-beek, D. Bouvier et al., The Galaxy platform for accessible, reproducible and collaborative biomedical analyses, Nucleic Acids Res, vol.46, pp.537-581, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01360125

L. B. Dickson, D. Jiolle, G. Minard, I. Moltini-conclois, S. Volant et al., Carryover effects of larval exposure to different environmental bacteria drive adult trait variation in a mosquito vector, Sci Adv, vol.3, issue.8, p.1700585, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01580399

B. Langmead, C. Trapnell, M. Pop, and S. L. Salzberg, Ultrafast and memory-efficient alignment of short DNA sequences to the human genome, Genome Biol, vol.10, issue.3, p.25, 2009.

A. Criscuolo and S. Brisse, AlienTrimmer: a tool to quickly and accurately trim off multiple short contaminant sequences from high-throughput sequencing reads, Genomics, vol.102, issue.5-6, pp.500-506, 2013.

J. Zhang, K. Kobert, T. Flouri, and A. Stamatakis, PEAR: a fast and accurate Illumina Paired-End reAd mergeR, Bioinformatics, vol.30, issue.5, pp.614-634, 2014.

N. A. Bokulich, B. D. Kaehler, J. R. Rideout, M. Dillon, E. Bolyen et al., Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin. Microbiome, vol.6, p.90, 2018.

E. Pruesse, C. Quast, K. Knittel, B. M. Fuchs, W. Ludwig et al., SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB, Nucleic Acids Res, vol.35, issue.21, pp.7188-96, 2007.

T. Z. Desantis, P. Hugenholtz, N. Larsen, M. Rojas, E. L. Brodie et al., Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB, Appl Environ Microbiol, vol.72, pp.5069-72, 2006.

J. Tang, I. D. Iliev, J. Brown, D. M. Underhill, and V. A. Funari, Mycobiome: approaches to analysis of intestinal fungi, J Immunol Methods, vol.421, pp.112-133, 2015.

K. Abarenkov, H. Nilsson, R. Larsson, K. Alexander, I. J. Eberhardt et al., The UNITE database for molecular identification of fungi-recent updates and future perspectives, New Phytol, vol.186, pp.281-286, 2010.

K. Findley, J. Oh, J. Yang, S. Conlan, C. Deming et al., Topographic diversity of fungal and bacterial communities in human skin, Nature, vol.498, pp.367-70, 2013.

P. Yarza, P. Yilmaz, E. Pruesse, F. O. Glöckner, W. Ludwig et al., Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences, Nat Rev Microbiol, vol.12, pp.635-680, 2014.

Q. Wang, G. M. Garrity, J. M. Tiedje, and J. R. Cole, Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy, Appl Environ Microbiol, vol.73, pp.5261-5268, 2007.

K. Katoh and D. M. Standley, MAFFT multiple sequence alignment software version 7: improvements in performance and usability, Mol Biol Evol, vol.30, issue.4, pp.772-80, 2013.

A. Criscuolo, S. Gribaldo, and . Bmge, Block Mapping and Gathering with Entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments, BMC Evol Biol, vol.10, issue.1, p.210, 2010.
URL : https://hal.archives-ouvertes.fr/pasteur-02445904

M. N. Price, P. S. Dehal, and A. P. Arkin, FastTree: computing large minimum evolution trees with profiles instead of a distance matrix, Mol Biol Evol, vol.26, issue.7, pp.1641-50, 2009.

C. Lozupone and R. Knight, UniFrac: a new phylogenetic method for comparing microbial communities, Appl Environ Microbiol, vol.71, pp.8228-8263, 2005.

D. Sims, I. Sudbery, N. E. Ilott, A. Heger, and C. P. Ponting, Sequencing depth and coverage: key considerations in genomic analyses, Nat Rev Genet, vol.15, pp.121-153, 2014.

P. J. Mcmurdie and S. Holmes, phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data, PloS ONE, vol.8, issue.4, p.61217, 2013.

C. Evans, J. Hardin, and D. M. Stoebel, Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions, Brief Bioinform, vol.19, issue.5, pp.776-92, 2017.

M. Dillies, A. Rau, J. Aubert, C. Hennequet-antier, M. Jeanmougin et al., A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis, Brief Bioinform, vol.14, issue.6, pp.671-83, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00782486

B. D. Ondov, N. H. Bergman, and A. M. Phillippy, Interactive metagenomic visualization in a Web browser, BMC Bioinformatics, vol.12, issue.1, p.385, 2011.

J. R. Conway, A. Lex, and N. Gehlenborg, UpSetR: an R package for the visualization of intersecting sets and their properties, Bioinformatics, vol.33, issue.18, pp.2938-2978, 2017.

V. Hourdel, S. Volant, D. P. O'brien, A. Chenal, J. Chamot-rooke et al., MEMHDX: an interactive tool to expedite the statistical validation and visualization of large HDX-MS datasets, Bioinformatics, vol.32, issue.22, pp.3413-3422, 2016.
URL : https://hal.archives-ouvertes.fr/pasteur-01377055

P. Vonaesch, E. Morien, L. Andrianonimiadana, H. Sanke, J. Mbecko et al., Stunted childhood growth is associated with decompartmentalization of the gastrointestinal tract and overgrowth of oropharyngeal taxa, Proc Natl Acad Sci, vol.115, issue.36, pp.8489-98, 2018.
URL : https://hal.archives-ouvertes.fr/pasteur-01925069

S. G. Acinas, R. Sarma-rupavtarm, V. Klepac-ceraj, and M. F. Polz, PCR-induced sequence artifacts and bias: insights from comparison of two 16S rRNA clone libraries constructed from the same sample, Appl Environ Microbiol, vol.71, issue.12, pp.8966-8975, 2005.

R. Sipos, A. J. Székely, M. Palatinszky, S. Révész, K. Márialigeti et al., Effect of primer mismatch, annealing temperature and PCR cycle number on 16S rRNA gene-targetting bacterial community analysis, FEMS Microbiol Ecol, vol.60, pp.341-50, 2007.