The overall distribution of
expression values obtained from RNAseq data is bimodal.
Not exact matches
«Barriers to
obtaining gene
expression profiling test heightened perceived
value.»
For every pair of tissues we
obtain the common genes by intersecting genes that in both tissues have correlation
value of gene
expression with PMI.
For the regression analyses, the matrix of
expression values was
obtained for the samples of each tissue and then normalized with the normalize.quantiles function from the preprocessCore library43.
To compute the correlation
values of gene
expression and PMI without the covariates, a procedure similar to the above was used where Pearson correlation is
obtained between gene
expression and PMI
values (Supplementary Fig. 38).
The SpatialDE test fits the \ (\ sigma ^ 2 \) and \ (\ delta \) parameters to each genes observed
expression levels, and also compares the likelihood with a model that has no spatial variance (FSV = 0) to
obtain a significance level (p -
value).
After solving for a and c from these two conditions, we
obtain the desired RF
expression, RF (ΔTGr) = RFLGM -LCB- exp (− bΔTGr) − 1 -RCB- / -LCB- exp (− bΔTGr, LGM) − 1 -RCB-, [2] where ΔTGr, LGM is chosen to be − 24 °C from Fig. 2C and
values for b are taken from the fits of Eq.