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In RCARE, Known-RNA-editing-site-compare functions are functions which identifies RNA sites that are differentially edited between samples according to chromosome, position, and reference/alternative sequence.
The read counts (depth) mapped to a gene region was first normalized between samples according to the total read numbers mapped to coding sequences (CDS) reads and then according to gene length.
Finally, we investigated the protein composition of seminal fluid using an RF classification model that analysed differences in protein abundances between samples according to the potential mating rate treatment (number of females encountered).
We also used principal-component analysis (PCA) to examine the similarity between samples according to the components that explain most of the variance in the data as shown in Additional file 1: Figure S1.
A similar analysis was performed to identify differences in miRNA expression between samples according to T status (low vs high), N status (positive vs negative), M status, tumour stage (low vs high), tumour grade (high vs low), ER expression and HER2 amplification.
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In summary, PCA has been used to identify relationships between treated samples according to their gene expression and, also, to investigate possible relations between genes.
We were not able to find differentially expressed miRNAs between all samples, according to their histological classification.
*Statistically significant compared to control samples or between indicated samples according to Student's t-test (p<0.05).
We compared survival distributions between the samples according to diabetes status and key covariates using life table analysis and log rank tests.
Most of the samples are distributed along PC1 in accordance with the bee strain (1 or 2).There is no such division between the samples according to the month or year of bee venom collection.
We estimated global F-statistics and FST between pairs of samples according to Weir and Cockerham [ 47].
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