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Using a uniform dataset of 426 non-homologues proteins (BT426) they obtained a Matthews correlation coefficient of 0.43.
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In the PWING project, we expect to use quite a uniform dataset for comparison of the waves at different local times.
Data processing, including Irreproducible Discovery Rate (IDR) analysis, was done using a uniform data processing pipeline for both datasets.
Instead of using a uniform randomization in [−1,+1] for all datasets, tuning the scaling of the uniform randomization range for each dataset enhances the overall performance.
When we repeated our analysis of 4-taxon datasets for branch lengths of 1.4 substitutions/site using a uniform prior with bounds of 0 to 1.5, branch lengths were less underestimated (median of 15% vs. 33%) than with a uniform prior with an upper bound of 1, as expected (results not shown).
The datasets we use were created by the ENCODE Analysis Working Group AWGG) using a uniform analysis pipeline.
For branches ≤ 0.2 substitutions/site for the 4-taxon HKY datasets, branch length estimation was similar in accuracy when using a uniform prior as when using the default exponential prior with mean equal to 0.1.
The data were collected using a uniform questionnaire.
Switching times were generated using a uniform distribution.
Data were collected using a uniform data sheet.
GI symptoms were systematically captured using a uniform research protocol.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com