variancePartition

[…] principal component analysis was performed in r with vegan [] on expressed root and shoot transcripts of plants and the eukaryotic microbiome. variance partition analysis was performed in r with variancepartition [] on root expressed transcripts of plant, the eukaryotic microbiome and phialocephala., the 19 shoot samples were used for qpcr to verify rna-seq gene expression calls using […]

[…] us to quantify the importance of neighbourhood interactions in driving bprs in young tree communities., all analyses were conducted in r (version 3.3.1) using the packages lme4, lmertest, mumin and variancepartition., data that support the findings of this study have been deposited in the bef-china project database (http://china.befdata.biow.uni-leipzig.de/) and are available […]

[…] it is possible to (partially) correct for some variables. to decompose gene expression into the percentage attributable to multiple biological and technical sources of variation, we applied variancepartition (fig. ). for each gene we calculated the percentage of expression variation attributable to cell type, donor, diagnosis, sex, as well as ctc scores for both fibroblast sets. […]

[…] each gene. multidimensional scaling analysis was used to identify outlier rna-seq samples, resulting in removal of one sample (supplementary fig. ) from the discovery cohort. in addition, we used variancepartition, to assess the contribution of technical and biological factors to variation in gene expression across the samples. this revealed minimal influence of age and gender (supplementary […]

[…] revealed that rin and pmi had strong widespread effects on gene expression (p < 0.01) (supplementary figure ). since the effects of one covariate could mask the effects of others, we used variancepartition to decompose gene expression variation into the variance attributable to each covariate. we calculated the variance explained by each covariate for each gene, which confirmed […]