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Another striking aspect of the congruence between these datasets is the different time scales over which samples were collected.
The second source of disagreement between these datasets is that different strategies for alignment of reads have an impact on the upper threshold for what is regarded as a small InDel.
To ensure that the coverage and dynamic range between these datasets is comparable, as we used different RNA-seq protocols, we first compared our eight-cell male embryos (n = 6) to eight-cell male embryos profiled by Deng et al., (n = 4), establishing a high degree of correlation between these profiles (Additional file 2: Figure S3, ρ =0.84, p-value < 2.2 × 10−16).
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The number of identical sequences between these datasets was determined using a Perl script and divided by the sum of number of complete transcripts in both datasets.
The correlation between EDM and COR for these datasets are the same as those given in Table 2. (− Not Sig., * P < 0.05, ** P << 0.001).
Finally, the total number of non-rRNA fragments for these datasets was between 4 and 6 million, significantly less than in the EDL933 datasets.
The probe sets found to overlap between the Se toxicity set and these datasets were then removed to enrich the data with Se-specific transcripts.
One important difference between the datasets is the mean of accuracy and maxF1.
The primary difference between the datasets is presence of Ca2+ cation in the medium.
A direct comparison between these two datasets is difficult however, because the A. niger paper treated the fungus with 20 mM DTT for 2 h and fractionated mRNAs based upon occupancy with < 2 and ≥2 ribosomes [ 28], whereas our study used 1 mM DTT for 1 h and fractionation into pools associated with <5 and ≥5 ribosomes.
Both of these findings support the idea that discrepancies between the datasets are related to differences in assay sensitivity, not the validity of targets.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com