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To this end, we utilized a pooled restriction site associated DNA sequencing (RAD-seq) approach [ 72] to generate polymorphism data of >30,000 single nucleotide sites across the genome of 10 three-spined stickleback populations in the Baltic Sea, and subjected the data to various outlier analyses, including BAYENV [ 73], which tests for associations between outliers and environmental parameters.
Unfortunately, we have not found any common statistical correlation between outliers and IC50 values.
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As such, we insist that insurers consider the circularity of private hospitals when choosing between outlier payment and patient dumping policies.8.8
We used the spearman correlation method to detect negative correlations between outlier miRNAs and outlier genes.
The p-value for the difference of overlapping between outlier genes and GeneGO's enriched pathways was 2.77e-07 by paired t-test.
The average distance between outlier SNPs was around 300,000 bp in scaffolds 1 and 3 and around 220,000 bp in scaffold 21.
Even though we find some evidence of high ILD between SNPs among the same regions, the most notable findings of ILD are between outlier SNPs on LG1 and 2 and between outlier SNPs on LG2 and 4 (supplementary table S3, Supplementary Material online).
In this study, the distance between outlier markers and candidate genes was considerable (between 100 and 3,000 Kb) and might exceed the window of linkage disequilibrium around selected genes.
The different patterns for the two stroke hospitals in the present study, however, indicate that there are differences between outlier hospitals that should be reflected in the quality improvement protocols.
The closest distance between outlier SNPs was 9000 bp in scaffold 1, 19,000 bp in scaffold 21 but around 125,000 bp in scaffold 3. We examined the patterns of genomic diversity across life cycle stages in European eel, using a combined approach of candidate coding-gene SNPs and a large-scale genomic analysis of 153,423 SNPs generated by RAD sequencing.
These methods propose various ways of defining a cutoff between outlier and non-outlier samples for a single gene, motivated by the fact that different oncogenes may be activated in different tumor subtypes, leading to outlier expression for these genes in some samples but not others [ 34- 38, 40].
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