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The mean difference between microarray estimates and individual genotyping was.077.077
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Nonetheless, the absolute mean difference between microarray estimates of pooled allele frequencies and NetAffx™ population allele frequencies was 0.094 but varies widely (Min 0.00, Max 0.619).
When k correction was applied, the correlation between k-corrected microarray estimates and individual genotyping increased to 0.986, and the mean difference between k-corrected microarray estimates was attenuated from.077 to.036.
The mean difference between k-corrected microarray estimates and NetAffx™ is also attenuated from.094 to.064.
Third, even though the correlations between results of qPCR and microarray estimates can be considered to be modest, these correlations are consistent with those reported in literature [ 50].
Another constraint was the ratio between housekeeping and tissue specific genes: from microarray estimates in Homo sapiens housekeeping genes represent about 5 7%% of the total [ 7], but there is no evidence that the human estimate applies also to the other species.
The concordance of our RNA-seq based estimates with previous microarray-based data from other bird species is in contrast with findings from Xiong et al. 2010 [ 22] who report a striking difference between microarray and RNA-seq based estimates of X- to autosomal expression ratios.
Similarity between microarray probes and probed DNA was estimated via probes of alleles of marker genes gyrB, mutS, and recA spotted on the microarray.
Spearman's rank correlation was used to estimate the degree of association between microarray and qRT PCR data for SCGB2A1, CLDN3, CLDN4, TROP-2 and SCGB1D2.
Spearman's rank correlation was used to estimate the degree of association between microarray and qRT-PCR data for TFF3 gene.
Because microarray platforms use their own element IDs rather than common gene IDs, two search tools were developed to determine the relationship between microarray elements and rice genes.
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