Sentence examples for inaccurate gene expression from inspiring English sources

As reads from a foreign sample would lead to inaccurate gene expression estimates, we removed these samples from downstream analysis, resulting in a final data set of 57 samples, comprising 21 controls and 36 cases.

Carrying out this step can be challenging because (1) gene functional annotation are often incomplete or inaccurate, (2) gene expression profiles are often limited to a subset of the genes or specific events during the cell cycle and (3) genome-wide expression data can be incomplete.

These choices can lead to inaccurate estimates of gene expression level and thus false inferences [ 36].

Differential expression analysis methods rarely consider probe redundancy, which can lead to inaccurate inference about overall gene expression or cause investigators to overlook potentially valuable information about differential regulation of variant mRNA products.

Such specific, rapid, and uncontrolled degradation of the Cy5 dye results in inaccurate and highly variable gene expression measurements.

We retained only those genes without distant alternative TSS (> 200 bp distance from the major TSS) and without ambiguous 3' UTR regions to avoid the potential inaccurate mapping of the gene expression data and gene structures.

Gene expression was normalized against expression of the GhEF1α gene.

Here we report that these alterations in control gene expression by GATA transcription factors lead to inaccurate normalization of transfection efficiency, which can be circumvented by using a modified Renilla luciferase expression plasmid.

The expression levels estimated for these genes will be particularly inaccurate because experimental error in the measurement of the sample with lower gene expression will lead to enormous variance in the ratios observed.

Therefore, GAPDH is inaccurate to normalize mRNA levels in studies investigating the effect of bisphosphonates on gene expression and it should be avoided.

Problems associated with inaccurate mapping can be more difficult to identify, but include bias in the quantification of differential gene expression, poor statistical power when detecting sequence variants, or greater noise and complexity when de-convoluting genomic re-arrangements.