Raw sequencing reads and supporting information for "A positive association between gut microbiota diversity and vertebrate host performance in a field experiment"

This dataset contains raw Illumina sequencing reads (MiSeq 600) of the V4 region of the 16S rRNA gene (515Fx806R) as well as R scripts and data files used for analyzing the bacterial gut microbiota of threespine stickleback fish (Gasterosteus aculeatus). These files are accompanying our manuscript titled: "A positive association between gut microbiota diversity and vertebrate host performance in a field experiment". Please find a more detailed description below. Raw sequencing data R files The file 'stickle_fitness_srs_normalization.R' contains R code for SRS-normalization of read counts according to Beule & Karlovski (https://peerj.com/articles/9593/). The file 'stickle_fitness_analysis.R' contains R code for all analyses associated with this manuscript. Data files The file 'alphadiv_srs.csv' contains metadata (lake, ecotype, pond, fitness group), stable isotope data (carbon and nitrogen signatures), sequencing read numbers as well as alpha diversity values for three metrics (ASV richness, Shannon diversity, Faith's phylogenetic dievrsity) for all samples. The files 'bc_dm.csv', 'uwuf_dm.csv', and 'wuf_dm.csv' are distance matrices based on Bray-Curtis dissimilarity, unweighted UniFrac and weighted UniFrac metrics. The files 'bc_pcoa.csv', 'uwuf_pcoa.csv', and 'wuf_pcoa.csv' contain PCoA scores based on Bray-Curtis dissimilarity, unweighted UniFrac and weighted UniFrac metrics. The file 'rooted_tree.nwk' is a rooted bacterial phylogeny used for calculating the UnIFrac metrics. The file 'qiime2_workflow.txt' contains all qiime2 scripts used for data analysis. The file 'stickle_fitness_SE_manifest.tsv' represents the manifest file used for importing sequencing data into qiime2. The file 'feature_table.biom' file is the ASV table exported from qiime2, which was converted into the tsv file 'feature_table.tsv'. The tsv file was further converted into the 'feature_table.csv' file, which represents the input for the 'stickle_fitness_srs_normalization.R' file. The 'feature-table_srs.csv' file represents the output of the 'stickle_fitness_srs_normalization.R' file, which was then converted into the 'feature-table_srs.tsv' file that was imported into qiime2 for downstream analyses. The 'stickle_fitness_metadata_sub_qiime2.tsv' file contains the subset of samples that had at least a minimum of 2500 sequencing reads. The 'silva_138_99_515-806_classifier.qza' file represents a trained taxonomic classifier.