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We used the affy package in Bioconductor [35] to read in and normalize the microarray measurements for each RNA type.
We searched public microarray measurements for genes that were specifically highly expressed in PaC.
Microarray measurements for four of the studied genes were verified by real time PCR.
At the same time there is no sign of anomalous differences between the QPCR and microarray measurements for the corresponding wheat expression (Panel B, Figure 5).
To evaluate the RNA-seq gene expression measurements, we compared them to normalized expression microarray measurements for 6,169 genes that could be uniquely identified on both platforms.
Hence, we confirmed fasting-mediated regulation of all genes selected for qPCR validation in all three tissues and show a strong correlation with the microarray measurements for all these genes.
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Suppose x ij is the microarray measurement for the ith probe (SNP) at the jth sample and y j depends on the class to which the jth sample belongs, then y i = 1 (j ∈ blood ) 2 (j ∈ normal tissue ). 3 (j ∈ tumor ) The Pearson and Spearman correlation coefficient for the ith probe (SNP) was then computed between x ij and y j.
Likewise, we only considered TFs expressed by cells growing in rich media (David et al. 2006), the experimental condition used for the microarray measurements of gene expression.
For the corresponding microarray measurements of these transcripts, we used Student's t-test to check the statistical significance that these transcripts are differentially expressed between both samples.
By comparison the Pearson correlations for the microarray measurements with TaqMan for these same 217 genes were Affymetrix (0.75), Agilent (0.80), and Illumina (0.73).
Typically, microarray measurements are given for 'probes' (that encode possibly multiple genes).
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