Journal: PLoS ONE

Article Title: Primed to vocalize: Wild-derived male house mice increase vocalization rate and diversity after a previous encounter with a female

doi: 10.1371/journal.pone.0242959

Figure Lengend Snippet: Classification of USVs: USV types, their abbreviations, a spectrogram’s example and definitions following the classification of [ , – ].

Article Snippet: Spectro-temporal features of USVs: slope (GLMM) , , , , , , , Relative Likelihood.

Techniques:

Journal: PLoS ONE

Article Title: Primed to vocalize: Wild-derived male house mice increase vocalization rate and diversity after a previous encounter with a female

doi: 10.1371/journal.pone.0242959

Figure Lengend Snippet: Approximately half of the males emitted less than 50 USVs during the 10 min trials, though some mice were very vocal (n = 50).

Article Snippet: Spectro-temporal features of USVs: slope (GLMM) , , , , , , , Relative Likelihood.

Techniques:

Journal: PLoS ONE

Article Title: Primed to vocalize: Wild-derived male house mice increase vocalization rate and diversity after a previous encounter with a female

doi: 10.1371/journal.pone.0242959

Figure Lengend Snippet: Boxplots of the number of USVs emitted by unprimed (control) and primed males. Boxes around the median (horizontal line) show the interquartile range (quartile 1 to 3) and whiskers extend to 1.5 times this range, or to the most extreme point, whichever is closer to the median. Extreme points are shown as circles. Different letters denote significant differences (p<0.05).

Article Snippet: Spectro-temporal features of USVs: slope (GLMM) , , , , , , , Relative Likelihood.

Techniques: Control

Journal: PLoS ONE

Article Title: Primed to vocalize: Wild-derived male house mice increase vocalization rate and diversity after a previous encounter with a female

doi: 10.1371/journal.pone.0242959

Figure Lengend Snippet: Tables 1 to 5 are regression tables of effects of priming on various aspects of vocalization in male mice.

Article Snippet: Spectro-temporal features of USVs: slope (GLMM) , , , , , , , Relative Likelihood.

Techniques:

Journal: PLoS ONE

Article Title: Primed to vocalize: Wild-derived male house mice increase vocalization rate and diversity after a previous encounter with a female

doi: 10.1371/journal.pone.0242959

Figure Lengend Snippet: The two spectrograms show a 10 s continuous sequence of the males that emitted most USVs in both groups, (A) the unprimed group and (B) in the group recorded 1d after priming. All lines of the spectrograms are continuous and each line shows 2 s (50 ms interval) of the 10 s sequence. Y-axes represent frequencies between 0–150 kHz with intervals of 25 kHz. Letters indicate examples of vocalization types, following the definitions and abbreviations in . LFV = low-frequency vocalization.

Article Snippet: Spectro-temporal features of USVs: slope (GLMM) , , , , , , , Relative Likelihood.

Techniques: Sequencing

Journal: PLoS ONE

Article Title: Primed to vocalize: Wild-derived male house mice increase vocalization rate and diversity after a previous encounter with a female

doi: 10.1371/journal.pone.0242959

Figure Lengend Snippet: Regression table of effects of priming on the spectro-temporal features of USVs in male mice.

Article Snippet: Spectro-temporal features of USVs: slope (GLMM) , , , , , , , Relative Likelihood.

Techniques:

Journal: Epigenetics

Article Title: Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples

doi: 10.1080/15592294.2022.2044127

Figure Lengend Snippet: Numbers of differentially methylated cytosines and regions associated with each covariate. Column 1 contains the experimentally determined threshold values for spatially adjusted P values and column 2 contains the corresponding numbers of CpG sites within differentially methylated regions (DMRs). The threshold is set such that the number of findings associated with a permuted version of the covariate would be less than 5% of the number of findings associated with the original covariate (column 2). The DMRs in column 3 are defined as described in Methods, filtering for the concordance of the direction of difference. Column 5 contains the numbers of differentially methylated cytosines (DMCs) detected without spatial adjustment (Benjamini-Hochberg-corrected PQLseq P value < 0.05), some of which belong to differentially methylated regions, and column 4 contains a subset of the DMCs in column 5. *Threshold 4.67E-07 (that was estimated to correspond to FDR 0.05 based on three permutations of sex) would correspond to FDR 0.0528 based on 10 permutations of sex.

Article Snippet: The reason why we chose a GLMM (PQLseq) that was fit separately for each CpG site [ ], followed by a simple Stouffer-Lipták-Kechris correction for the spatial adjustment, was computational efficiency compared to other approaches and the ability to include both binary and continuous covariate effects.

Techniques: Methylation, Control, Transformation Assay

Journal: Epigenetics

Article Title: Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples

doi: 10.1080/15592294.2022.2044127

Figure Lengend Snippet: The numbers of differentially methylated CpG sites associated with each original and permuted covariate would have been these, if the default significance threshold (Benjamini-Hochberg corrected spatially adjusted P value < 0.05) had been applied. These numbers were obtained by performing a differential methylation analysis (fitting a GLMM to obtain a Wald test P value for each CpG site, followed by the spatial adjustment and multiple testing correction implemented within RADMeth) for the original input data, as well as for 45 permuted design matrices (3 permutations of each of the 15 covariates of interest). This permutation analysis showed that the spatially adjusted P values were inflated.

Article Snippet: The reason why we chose a GLMM (PQLseq) that was fit separately for each CpG site [ ], followed by a simple Stouffer-Lipták-Kechris correction for the spatial adjustment, was computational efficiency compared to other approaches and the ability to include both binary and continuous covariate effects.

Techniques: Methylation

Journal: Epigenetics

Article Title: Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples

doi: 10.1080/15592294.2022.2044127

Figure Lengend Snippet: Numbers of DMCs and DMRs associated with permuted covariates (false discoveries), when RADMeth’s spatial adjustment and default DMC/DMR detection criteria were applied on P values from a beta-binomial regression model for each CpG site (the RADMeth model, column 1) or P values from PQLseq (column 2). DMCs are defined as CpG sites with Benjamini-Hochberg corrected spatially adjusted P value < 0.05, and DMRs are genomic regions with two or more consecutive Benjamini-Hochberg corrected spatially adjusted P values < 0.01 (default criteria in the current implementation of RADMeth within MethPipe version 3.4.3). Full model is the model used in the actual differential methylation analyses, including clinical and technical covariates specified in the Supplementary Table 1. The simple models were permuted sex + PC1 + PC2 and permuted epidural + sex + PC1 + PC2. These analyses were run for three permutations of each covariate.

Article Snippet: The reason why we chose a GLMM (PQLseq) that was fit separately for each CpG site [ ], followed by a simple Stouffer-Lipták-Kechris correction for the spatial adjustment, was computational efficiency compared to other approaches and the ability to include both binary and continuous covariate effects.

Techniques: Methylation

Journal: Epigenetics

Article Title: Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples

doi: 10.1080/15592294.2022.2044127

Figure Lengend Snippet: Comparison between results obtained using PQLseq (a GLMM) and RADMeth beta-binomial regression. Here, DMCs are defined as CpG sites with Benjamini-Hochberg corrected P value < 0.05 (before spatial adjustment) and CpGs within candidate DMRs are all CpG sites with empirically FDR-controlled spatially adjusted P value < 0.05. DMR detection has not been done for this comparison. The full models include all technical and clinical covariates specified in the Supplementary Table 1, and the simple model is sex + PC1 + PC2. The percentages are percentages of the detections of PQLseq.

Article Snippet: The reason why we chose a GLMM (PQLseq) that was fit separately for each CpG site [ ], followed by a simple Stouffer-Lipták-Kechris correction for the spatial adjustment, was computational efficiency compared to other approaches and the ability to include both binary and continuous covariate effects.

Techniques: Comparison

Journal: Epigenetics

Article Title: Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples

doi: 10.1080/15592294.2022.2044127

Figure Lengend Snippet: A summary of RRBS and Pyrosequencing results on the association between sex (0 = male, 1 = female) and six CpG sites located on the promoter of Zona Pellucida Binding Protein 2 (ZPBP2). The RRBS data was modelled with a GLMM (PQLseq), and the pyrosequencing data was modelled with ordinary linear regression, as described in Methods.

Article Snippet: The reason why we chose a GLMM (PQLseq) that was fit separately for each CpG site [ ], followed by a simple Stouffer-Lipták-Kechris correction for the spatial adjustment, was computational efficiency compared to other approaches and the ability to include both binary and continuous covariate effects.

Techniques: Binding Assay