We used RNAseq analysis to extract total circulating cell-free RNA from fifty-eight blood samples from both conditioned and non-conditioned individuals. To ensure data quality, we subjected the 28.80 GB of data within these 58 libraries to rigorous quality control measures. Subsequently, these samples were employed for both RNAseq and miRNA analysis.
Given the relatively poor data quality, we analyzed contamination using the "Fastq-screen" software (v0.14.1). This involved mapping randomly selected reads to various reference genomes to identify common contaminants. After confirming a sufficient number of unique reads for our target organism, we proceeded to eliminate ribosomal RNA (rRNA), despite the use of an rRNA depletion kit ("SMART-Seq stranded") during sample preparation. We employed the "SortMeRNA" software (v.4.3.4) to map all libraries to an rRNA database to achieve this. Fortunately, we retained enough reads after this quality control step to proceed with the differential expression analysis.
The MDS plot visually represents our miRNA analysis (in purple) and RNA analysis (in green). Notably, the plot consistently demonstrates a clear division between the 'A' and 'B' groups within both datasets.
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