MOESM4 of “Gap hunting” to characterize clustered probe signals in Illumina methylation array data

Additional file 4: Table S2. Breakdown of all C/G and SBE site measured polymorphism scenarios. We isolated specifics scenarios in which the following conditions were met: a probe contained a measured SNP that mapped to the C, G, or SBE sites of a probe, and it also did not contain any other form of mapping SNP. This table contains a list of all SNP C, G and SBE site scenarios herein and their corresponding Figure #. Also included is the number of probes analyzed for each scenario, along with the count and proportion of those probes that were classified as gap signals. Most probes in SEED that overlapped with measured SNPs were not classified as gap signals (though ~80% of gap signals did overlap with SNPs, see Additional file 7)

MOESM3 of “Gap hunting” to characterize clustered probe signals in Illumina methylation array data

Additional file 3: Table S1. Distribution of group counts for gap signals in SEED. Breakdown of number of groups or clusters in the 11,007 gap signals found in SEED samples

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Additional file 9: Table S3. Group distributions of 3 different classifications of gap signals. We compared the group distribution for the three groups—mapping measured SNP, mapping annotated SNP, and no mapping SNP—of gap signals. The two groups with mapping SNPs had a very similar relative proportion of groups, while the group with no mapping SNPs was comparatively enriched for distributions with 2 clusters or groups. This result lends additional rationale to a different mechanism besides SNPs as leading the gap signal behavior

MOESM11 of “Gap hunting” to characterize clustered probe signals in Illumina methylation array data

Additional file 11: Figure S34. Filtering on variably methylated probes at various cutoffs in the context of gap signals. We calculated the proportion of gap and non-gap signals at various percentile thresholds of standard deviation cutoff (1–99%) to define a variably methylated probe. Researchers who filter on variable methylation prior to association analysis should be cautioned to be increasingly aware of gap signals (and subsequently their implications on DNAm related to disease described herein) as the cutoff to define a variably methylated probe increases

Additional file 1 of Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

Figures S1-S2. Depiction of surrogate variable selection process for SEED (S1) and SSC (S2). Panel A: Heatmap indicating degree of association with known potential technical variables or confounders with estimated surrogate variables. Panel B: Inflation factor (lambda) calculated for progressively including surrogate variables in association models. The number of surrogate variables to include in the ultimate association testing model was to determine to be that which properly controlled the inflation factor and adequately captured known technical variables or confounders. See “Methods” for additional explanation. (PDF 19 kb

Additional file 2 of Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

Table S1. Demographic characteristics for samples in the SSC (S2) dataset. (XLSX 11 kb

Young Muslims and Exclusion - experiences of 'othering'

Research we completed in 2016 with 19 Muslim university students in London and Birmingham suggests they often feel exclusion most strongly after such events. The exclusionary experiences our participants faced took place on public transport, in the streets, at work, and at school and university. They included a combination of both subtle and direct experiences of exclusion; for example, from a London participant noticing that no-one would sit next to her on the tube to a Birmingham participant having a woman refuse to move her bag so she could sit down on the bus and directly accusing her of causing terrorism – both following the 2015 Paris attacks. The significance of ‘dressing Muslim’, particularly through wearing the hijab, emerged in the narratives of the young women we spoke to, with them often reporting to be perceived in ways that other them such as ‘foreigner’, ‘problematic’ and even as ‘extremist’. Other scholars have suggested that Muslim young people and communities struggle with these ‘othering’ discourses which are communicated through media and policy as well as experienced in their everyday lives (see Ahmed, 2015; Jeldtoft, 2012; Khan, 2013). Khan (2013) refers to this process as ‘theyification’ which he argues is consolidated by policy, practice and even research. The examples from our research are explored in two articles we have submitted to other journals: ‘“I just love the Queen” Positioning in Young Muslim Discourse’ (Pihlaja and Thompson, forthcoming in Discourse, Context and Media) and ‘Temporary liberties and uncertain futures: perceptions of young Muslim women on life in Britain’ (Thompson and Pihlaja, under review). Here, we explore an example that has not been included in these other articles. In the extract explored in detail below, Habiba (a pseudonym), an African Muslim of Somali heritage, explains her shock at being labelled a racist by another Black woman, and her feelings at being ‘othered’ by her because of her clothing

Additional file 4 of Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

Table S3. Concordance between suggestively associated (p < 1 × 10− 4) CpG sites in peripheral blood and their corresponding effect sizes in three brain regions. (CSV 3 kb

Additional file 3 of Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

Table S2. Full summary statistics and meta-analysis results for all 445,608 CpG sites that were present in both the cleaned SEED and SSC datasets. (CSV 40707 kb

Additional file 5 of Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

Figures S3. Quadrant plots depicting concordance in effect sizes between suggestively associated (p < 1 × 10− 4) CpG sites in peripheral blood and three brain regions. A) Prefrontal cortex B) Temporal Cortex C) Cerebellum. Points in red indicate those sites with p < 1 × 10− 5 in peripheral blood. (PNG 21 kb