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- W4248179965 abstract "Abstract Objectives: DNA methylome and RNA transcriptome studies are growing, but investigators have to consider the cell type composition of tissues used. In blood samples, for instance, data reflect picture of mixture of cells. Specialized algorithms address the cell-type heterogeneity issue. We tested if the estimation of cell type composition in the blood are correlated between two heterogeneous datasets. Results: We used methylome and transcriptome datasets obtained from a cohort of ten individuals whose blood were sampled at two different timepoints and examined how the cell composition derived from these omics correlated with each other using “CIBERSORT” for transcriptome and “EstimateCellCounts function” for the methylome. The correlation coefficients between the two omic datasets range from 0.45 to 0.81. There was minimal correlation between the two timepoints using the same algorithm. Our results suggest that a posteriori corrections of a mixture of cells present in blood samples are reliable. Using an omic dataset to correct a second dataset for relative fractions of cells seems to be appropriate, but only when the samples are simultaneously collected. Such approach could be beneficial when there are difficulties to control the cell types in the second dataset, even when the sample size is limited." @default.
- W4248179965 created "2022-05-12" @default.
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- W4248179965 date "2019-08-14" @default.
- W4248179965 modified "2023-09-28" @default.
- W4248179965 title "Reliability and correlation of mixture cell correction in methylomic and transcriptomic blood data" @default.
- W4248179965 doi "https://doi.org/10.21203/rs.2.12836/v1" @default.
- W4248179965 hasPublicationYear "2019" @default.
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