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This highlights the importance of controlling for coverage bias when investigating sequencing data for applications such as RNA-Seq, CNV identification or whole genome sequencing.
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After controlling for publication bias, results were no longer significant.
This screening reduced the number of non-synonymous SNPs in high coverage TUGs, removed the dependence of dn/ds on coverage, and removed the need to control for sampling biased by depth (i.e. coverage; see [ 76, 77]).
Next, to control for ascertainment bias related to variable read depth, or in this case expression level and mapping success, we adjusted length-corrected SND counts using the read-depth correction (eq. 7) proposed by Jiang et al. [39] that accounts for the possibility of missing data at low coverage sites and the probability of observing a mutant allele in a given sample.
We used propensity scoring to control for selection bias.
It is therefore difficult to control for treatment bias and selection bias.
Although BRFSS weighting procedures are assumed to control for non-coverage and non-response bias it may be inadequate to control for certain types of selection bias.
We also controlled for lead-time bias in this analysis.
The single blinded RCT helped to control for bias.
It also controls for potential biases.
Not controlling for these characteristics might lead to biased results.
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CEO of Professional Science Editing for Scientists @ prosciediting.com