Supplementary Information from A novel Bayesian approach to predicting reductions in HIV incidence following increased testing interventions among gay, bisexual and other men who have sex with men in Vancouver, Canada

Increasing HIV testing rates among high-risk groups should lead to increased numbers of cases being detected. Coupled with effective treatment and behavioural change among individuals with detected infection, increased testing should also reduce onward incidence of HIV in the population. However, it can be difficult to predict the strengths of these effects and thus the overall impact of testing. We construct a mathematical model of an ongoing HIV epidemic in a population of gay, bisexual and other men who have sex with men. The model incorporates different levels of infection risk, testing habits and awareness of HIV status among members of the population. We introduce a novel Bayesian analysis that is able to incorporate potentially unreliable sexual health survey data along with firm clinical diagnosis data. We parameterize the model using survey and diagnostic data drawn from a population of men in Vancouver, Canada. We predict that increasing testing frequency will yield a small-scale but long-term impact on the epidemic in terms of new infections averted, as well as a large short-term impact on numbers of detected cases. These effects are predicted to occur even when a testing intervention is short-lived. We show that a short-lived but intensive testing campaign can potentially produce many of the same benefits as a campaign that is less intensive but of longer duration

Additional file 1: Figure S1. of SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations

Schematic of bootstrap re-sampling procedure. (PNG 146 kb

Additional file 8: Figure S3. of SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations

Random module stability. To get a sense of the stability that could be expected of a module containing genes with minimal relation to each other, a simulation study was carried out. Modules of size 50, 100, 150, 200, 250, 300, 350, and 400 were randomly assembled by sampling from the all 2512 gene symbols in the filtered dataset. This was done 100 times for each size of module. For each random module, their best match Jaccard similarity ceofficients were computed for each of the 1000 bootstrap results previously generated, and the resulting distribution was summarized using the h-index. (PNG 51 kb

Additional file 2: Table S1. of SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations

Patient demographics. Demographic characteristics of the 238 COPD patients. (CSV 495 bytes

Variation in RNA-Seq Transcriptome Profiles of Peripheral Whole Blood from Healthy Individuals with and without Globin Depletion

<div><p>Background</p><p>The molecular profile of circulating blood can reflect physiological and pathological events occurring in other tissues and organs of the body and delivers a comprehensive view of the status of the immune system. Blood has been useful in studying the pathobiology of many diseases. It is accessible and easily collected making it ideally suited to the development of diagnostic biomarker tests. The blood transcriptome has a high complement of globin RNA that could potentially saturate next-generation sequencing platforms, masking lower abundance transcripts. Methods to deplete globin mRNA are available, but their effect has not been comprehensively studied in peripheral whole blood RNA-Seq data. In this study we aimed to assess technical variability associated with globin depletion in addition to assessing general technical variability in RNA-Seq from whole blood derived samples.</p><p>Results</p><p>We compared technical and biological replicates having undergone globin depletion or not and found that the experimental globin depletion protocol employed removed approximately 80% of globin transcripts, improved the correlation of technical replicates, allowed for reliable detection of thousands of additional transcripts and generally increased transcript abundance measures. Differential expression analysis revealed thousands of genes significantly up-regulated as a result of globin depletion. In addition, globin depletion resulted in the down-regulation of genes involved in both iron and zinc metal ion bonding.</p><p>Conclusions</p><p>Globin depletion appears to meaningfully improve the quality of peripheral whole blood RNA-Seq data, and may improve our ability to detect true biological variation. Some concerns remain, however. Key amongst them the significant reduction in RNA yields following globin depletion. More generally, our investigation of technical and biological variation with and without globin depletion finds that high-throughput sequencing by RNA-Seq is highly reproducible within a large dynamic range of detection and provides an accurate estimation of RNA concentration in peripheral whole blood. High-throughput sequencing is thus a promising technology for whole blood transcriptomics and biomarker discovery.</p></div

Deconvolution of the lymphocyte compartment of peripheral whole blood elucidates patterns of differential composition, and differential cell type-specific gene expression, between AR and NR subjects before, during and after an episode of treatable acute kidney allograft rejection.

<p>The composition of the peripheral whole blood samples was inferred from mixed expression data for all 48 subjects (24 AR, 24 NR) at the time of a treatable acute rejection episode, as well as at baseline (23 AR, 20 NR) and after rejection had resolved (20 AR, 19 NR) when expression data was available (<b>A</b>). The mean (and bootstrapped confidence intervals) of the proportions of neutrophils, B cells, CD4+, CD8+ T cells and NK cells are plotted for each group, at each time point. Significant differences between groups are labeled (Wilcoxon rank-sum test; p≤0.05 *, p≤0.01 **). Cell type specific differential expression analysis (csSAM) was performed using the sample composition information inferred above (<b>B</b>). Cell type-specific differential expression was assessed for all seven cell-types included in the basis matrix, but results are shown only for neutrophils, B cells, CD4+, CD8+ T cells and NK cells (no signal in monocytes, eosinophils). Cell types not detectable in more than 75% of subjects at a given time point were omitted from the model. For each time point, the number of probe-sets called significantly differentially expressed at various false discovery rate (FDR) values is plotted for the one-tailed up and one-tailed down hypotheses (red and blue lines, respectively). A cutoff FDR ≤0.30 was selected for discovery purposes (dashed line).</p

Gene set enrichment of cell type-specific gene lists – MsigDB C2 KEGG Canonical Pathways

<p>Gene set enrichment of cell type-specific gene lists – MsigDB C2 KEGG Canonical Pathways</p

Enrichment analysis of cell type-specific differentially expressed probe-sets establishes their plausibility.

<p>The tissue specificity of the cell type-specific gene lists identified in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095224#pone-0095224-g002" target="_blank">Figure 2</a> is assessed by visualizing their median enrichment across a wide range of tissues (<b>A</b>). Significance of enrichment of each cell type-specific gene list in each tissue is assessed by hypergeometric test (<b>B</b>).</p

Gene set enrichment of cell type-specific gene lists – MSigDB C7 Immunologic Signatures

<p>Gene set enrichment of cell type-specific gene lists – MSigDB C7 Immunologic Signatures</p

Globin depletion yields 3500 additional robustly detectable transcripts from a single representative peripheral whole blood RNA-Seq experiment.

<p>(A) Correlation plot of the transcript FPKMs of an exemplar biological sample, either globin depleted (y-axis) or not (x-axis). (B) Distribution of transcript FPKMs in the same exemplar biological sample, either globin depleted (blue) or not (red). Data is shown on a log scale. Significant FPKM cutoffs of 1, 2.5 and 1000 are marked by dashed line.</p