A number of Data objects are provided. These correspond to the experimental data that was analyzed, and underlying numeric values for several figures in the associated manuscript. Raw sequence data can be found in the appropriate repositories (GSE102248, PRJEB22060).
All.filtered Data frame of individual OD600 measurements for 440 strains that were assayed in vitro and that passed quality control. Assays were performed in 96-well plates and measurements were taken over 72 hours. Data frame columns are as follows:
Features Data frame of in vitro growth features for 440 strains. All of these values are calculated from the growth data in All.filtered. The data frame includes the following columns:
Strain.auc Raw area under the growth curve (AUC) for each of 440 tested strains. Row names indicate strain ID. Columns of the data frame are as follows:
gc.tree A phylo object that defines a phylogenetic tree of 395 strains that were tested in vitro, passed quality control, and ahad a full length 16S gene Sanger sequence.
binP.all Individual plant shoot phosphate content measurements for plant-bacterium binary assays involving 194 bacterial strains. Data frame columns are as follows:
binP Results of testing for the effect of individual bacterial strains on plant shoot phosphate accumulation in plant-bacterium binary assays. All results are derived from data in binP.all. Columns of the data frame are as follows:
Elongation Main root elongation measurements for individual plants treated with synthetic communities. Measurements where made from pictures in imageJ. Columns of the data frame are as follows:
Pi Plate level phenotypic measurement for plants treated with synthetic communities. Columns of the data frame are as follows:
Map.colonization: Metadata for samples that underwent microbial profiling via 16S gene sequencing. The columns of the data frame are as follows:
Tax.colonization Taxonomy and block allocation of bacteria used in synthetic community experiments. The columns of the data frame are as follows:
dge.wheel DGEList object. Full RNA-seq gene counts for synthetic community assays. The count matrix is also available at GEO together with the raw sequence data (GSE102248). See the documentation for the edgeR package for more details on the object.
wheelP.full A Dataset object. Contains the sequence counts of each strain on each sample that was profiled via 16S gene sequencing, as well as the sample metadata and strain taxonomic information. The counts were obtained by mapping all reads against all reference sequences. See the documentation of the AMOR package for more details on the object.
wheelP.mapsplit A Dataset object. Contains the sequence counts of each strain on each sample that was profiled via 16S gene sequencing, as well as the sample metadata and strain taxonomic information. The counts were obtained by mapping reads against reference sequences of strains added to each specific samples. See the documentation of the AMOR package for more details on the object.
wheelP.rna A Dataset object. Contains the sequence counts of each plant gene for each sample that was profiled via RNA-seq, as well as the sample metadata and strain taxonomic information. The counts were correspond to the counts in the dge.wheel object. See the documentation of the AMOR package for more details on the object.
m1.wheel A DGEGLM object. A fitted model of the RNA-seq data in dge.wheel. See the documentation for the edgeR package for more details on the object.
Below we describe some data objects that contain the numeric values that underlie several figures in the associated manuscript. All the numbers below were calculated from data in the above objects and is therefore redundant but it is provided for the sake of completeness.
cross.validation.error These are the numeric values underlying figure 7B. The numbers are the leave-synthetic community-out cross validation. For more details on its calculation please visit the sister repository wheelPi. The columns of the data frame are as follows:
group.colonization These are the numeric values underlying figures S6B-C and fig12. They were obtained directly from wheelP.mapsplit Dataset object. Columns of the data frame are as follows:
mds.colonization These are the numeric values that underlie figure S6A. They were calculated directly from Dataset wheelP.mapsplit. Columns of the data frame are as follows.
nn.sensitivity These are the numeric values underlying figure 7C. The numbers are the results of the sensitivity analysis on the different models. For more details on its calculation please visit the sister repository wheelPi. The columns of the data frame are as follows:
phen.additivity Numeric values underlying figure 4 and figure 5B. Calculated directly from the Elongation and Pi data frames. Columns of the data frame are as follows:
phen.presence.abundance Numeric values underlying figure S7. Calculated directly from the Elongation and Pi data frames, together with the wheelP.mapsplit Dataset. Columns of the data frame are as follows:
pi.phu.cfu Numeric values that underlie figure 2D and figure S3A. Directly obtained from the experimenter. Columns of the data frame are as follows:
prediction.error Theser are the numeric values underlying figure 7F. The numbers are the mean different prediction error for the validation experiments and each model. For more details on its calculation please visit the sister repository wheelPi. The columns of the data frame are as follows:
pre.treatments Numeric values underlying figure S3B. Directly obtained from the experimenter. Columns of the data frame are as follows:
signal.noise.ratio These are the numeric values underlying figure S11. The numbers are the signal and noise variances for each plant phenotype. The ratio of these variances (i.e. the signal to noise ratio) determines the feasibility of predictive modelling. For more details on its calculation please visit the sister repository wheelPi. The columns of the data frame are as follows:
validation.predicted.observed. These are the numeric values underlying figure 7E. The numbers are the predicted and observed plant shoot phosphate accumulation upon synthetic community block replacements. For more details on its calculation please visit the sister repository wheelPi. The columns of the data frame are as follows:
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