Journal: PLoS ONE

Article Title: Neuroinflammation, body temperature and behavioural changes in CD1 male mice undergoing acute restraint stress: An exploratory study

doi: 10.1371/journal.pone.0259938

Figure Lengend Snippet: The results of automated behaviour analysis (with HCS) showing behaviour from before and after exposure to restraint stress in mice undergoing each method of handling (NAH-T, TH or NAH-M). P-values refer to comparison between pre-post R&L stress on all animals. Walking and Rearing frequencies significantly declined following stress, although the Total Distance mice moved (metres) tended to decline, not significantly. The average duration of bouts (in seconds) of Grooming increased. Handling method had no significant effects.

Article Snippet: Automated behaviour analysis software ( www.cleversysinc.com ) was used to record the spontaneous unconstrained behaviour of the mice.

Techniques: Comparison

Journal: Clinical Epigenetics

Article Title: Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design

doi: 10.1186/s13148-022-01320-9

Figure Lengend Snippet: Distinction between two primary analysis methods in the present study. We employed both variance components and penalised regression models in order to examine the amount of phenotypic variance captured by each respective probe set (n = 18 in total, see Methods). Variance component estimates were obtained using the restricted maximum likelihood method in OSCA. Here, we were able to estimate the amount of phenotypic variance captured by all probes in a given probe set in the training sample (n ≤ 4450). We also employed penalised regression to build linear DNAm-based predictors of traits using probes in a given probe set in the training sample. We then applied the predictors to the test sample (n ≤ 2578) in order to estimate how much variance in a given trait the predictor could explain over basic covariates (such as age and sex). This coefficient reflected the incremental R 2 estimate and pertained to an out-of-sample setting as the predictor was applied to a sample outside of that in which it was derived. LASSO, least absolute shrinkage and selection operator; OSCA, OmicS data-based complex trait analysis. Image created using Biorender.com

Article Snippet: For this, we used OmicS-data-based complex trait analysis (OSCA) software in which the correlation structure among all input probes is used to create an omic-data-based relationship matrix (ORM).

Techniques: Derivative Assay, Selection

Journal: Clinical Epigenetics

Article Title: Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design

doi: 10.1186/s13148-022-01320-9

Figure Lengend Snippet: Variance captured in complex traits by all available probes and four subsets of decreasing size. Restricted maximum likelihood was used to estimate variance components in the training sample (n ≤ 4450, OSCA software). The four traits (out of seventeen biochemical and complex traits) with the highest proportion of variance captured by DNAm are shown. Five different sets of probes were compared. ‘All available probes’ denotes probes that were common to the Illumina EPIC and 450K arrays and passed quality control procedures in the training sample within Generation Scotland (n = 393,654 probes). The ‘variable non-mQTL probes’ set consisted of probes without reported non-genetic influences and mean Beta-values between 10 and 90%. The remaining three probe subsets contained the 50,000, 20,000 and 10,000 most variable non-mQTL probes (ranked by their standard deviations). The five sets of probes therefore had decreasing numbers of probes but increasing mean variabilities. Vertical bars show 95% confidence intervals. DNAm, DNA methylation; mQTL, methylation quantitative trait locus; OSCA, OmicS data-based complex trait analysis

Article Snippet: For this, we used OmicS-data-based complex trait analysis (OSCA) software in which the correlation structure among all input probes is used to create an omic-data-based relationship matrix (ORM).

Techniques: Software, Control, DNA Methylation Assay, Methylation