A goal is to utilize these more accessible sample types in order to be useful for diagnosis of respiratory infection.
To account for these differences, particle size, and sometimes additional organic matter, correction factors are often applied to the source soil concentrations in an attempt to make the two sample types more directly comparable.
Oral rinse samples yielded respiratory pathogens more frequently than other sample types (sensitivity 92%).
We hypothesized that milk fat samples, if dominated by exosomal RNA arising from milk-producing cells, would yield transcriptomes with greater similarity to each other compared with other sample types with more heterogeneous sources of RNA.
Our analysis replicated methods applied by Ye et al. (2011) and Preau et al. (2010) to partition the variance components among between-child, within-child between-day, and within-child within-day components for sample types with more than one sample per day (Table 3).
We also assume that there are indeed K cell types, that gene expression within each cell type is identical in all samples irrespective of the tissue composition, and that there are more samples than cell types (otherwise the error terms cannot be estimated), or that these assumptions are good approximations.
The main clustering in the left figure is eukaryote versus bacteria while the patterns in the right figure are more dominated by sample type with the eukaryote/bacteria samples mixed up.
Except for 15 (11%) species found only in GCF samples and 17 (13%) species found only in PP samples, the majority (N = 101, 76%) of the 133 species/phylotypes were identified in both sample types; 23 (23%) more often in GCF than PP samples and 58 (57%) more often in PP than GCF samples (Figure 3).
The ANOVA model could be extended to include more factors such as instrument types and the sample types.
A wide range of approaches that facilitate low abundance peptide detection have been investigated, with some techniques applicable to specific sample types (sample preparation16,17), while others are more broadly applicable (data acquisition7,10,18,19,20,21).
