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AdjP-value corresponds to p-value adjusted by the multiple test adjustment, during enrichment test.
adjP value adjusted by the multiple test adjustment (adjP) There were no overlap between the 228 DEG and genes from the 20q11.1 gain observed in the schizophrenic case.
The second row lists number of reference genes in the category (C), number of genes in the gene set and in the category (O), expected number in the category (E), ratio of enrichment (R), p value from hypergeometric test (rawP), and p value adjusted by the multiple test adjustment (adjP).
C- Reference genes in the category, O- number of genes in the gene set and also in the category, E- expected number in the category, R- ratio of enrichment, rawP- p value from hypergeometric test, adjP- p value adjusted by the multiple test adjustment.
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Therefore they are not influenced by the "multiple testing effect" or the "inflated error effect", and are highly suitable for detecting both effects.
In contrast, three of the genes tested (e.g., AP2/ERF114, NGATHA1, Nitrate Reductase 2) failed to demonstrate a significant difference as measured by the multiple test-corrected t-statistic, and a single transcript, a second Myb transcription factor-like b gene (7 root ESTs compared with 1 non-root EST), was determined to be 2.6-fold less abundant in roots than in shoots (p < 0.05).
This allowed us to detect associations that might have been removed as false positives by the multiple testing correction method applied to the SSR approach.
All p-values were corrected for the false-positives introduced by the multiple testing presented by many time points using Bonferroni correction and 10-3 waselecteded as the cut-off threshold for p-values.
This multivariate test provides an overall assessment of the observed tendencies in the data and is not affected by the multiple testing problems associated with the standard univariate testing procedures.
Moreover, this type of analysis can isolate gene pairs of interest for follow-up analysis without being burdened by the multiple testing corrections necessary for genome-wide SNP SNP pairwise interaction analysis.
We then performed a targeted analysis of cytokine genes by applying the multiple testing procedures to this subset after RMA processing was completed.
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