90 research outputs found
Graphical models for zero-inflated single cell gene expression
Bulk gene expression experiments relied on aggregations of thousands of cells
to measure the average expression in an organism. Advances in microfluidic and
droplet sequencing now permit expression profiling in single cells. This study
of cell-to-cell variation reveals that individual cells lack detectable
expression of transcripts that appear abundant on a population level, giving
rise to zero-inflated expression patterns. To infer gene co-regulatory networks
from such data, we propose a multivariate Hurdle model. It is comprised of a
mixture of singular Gaussian distributions. We employ neighborhood selection
with the pseudo-likelihood and a group lasso penalty to select and fit
undirected graphical models that capture conditional independences between
genes. The proposed method is more sensitive than existing approaches in
simulations, even under departures from our Hurdle model. The method is applied
to data for T follicular helper cells, and a high-dimensional profile of mouse
dendritic cells. It infers network structure not revealed by other methods; or
in bulk data sets. An R implementation is available at
https://github.com/amcdavid/HurdleNormal .Comment: Fixed error in software UR
Data Exploration, Quality Control and Testing in Single-Cell qPCR-Based Gene Expression Experiments
Cell populations are never truly homogeneous; individual cells exist in
biochemical states that define functional differences between them. New
technology based on microfluidic arrays combined with multiplexed quantitative
polymerase chain reactions (qPCR) now enables high-throughput single-cell gene
expression measurement, allowing assessment of cellular heterogeneity. However
very little analytic tools have been developed specifically for the statistical
and analytical challenges of single-cell qPCR data. We present a statistical
framework for the exploration, quality control, and analysis of single-cell
gene expression data from microfluidic arrays. We assess accuracy and
within-sample heterogeneity of single-cell expression and develop quality
control criteria to filter unreliable cell measurements. We propose a
statistical model accounting for the fact that genes at the single-cell level
can be on (and for which a continuous expression measure is recorded) or
dichotomously off (and the recorded expression is zero). Based on this model,
we derive a combined likelihood-ratio test for differential expression that
incorporates both the discrete and continuous components. Using an experiment
that examines treatment-specific changes in expression, we show that this
combined test is more powerful than either the continuous or dichotomous
component in isolation, or a t-test on the zero-inflated data. While developed
for measurements from a specific platform (Fluidigm), these tools are
generalizable to other multi-parametric measures over large numbers of events.Comment: 9 pages, 5 figure
MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data
Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at https://github.com/RGLab/MAST
The association of cancer survival with four socioeconomic indicators: a longitudinal study of the older population of England and Wales 1981–2000
BACKGROUND: Many studies have found socioeconomic differentials in cancer survival. Previous studies have generally demonstrated poorer cancer survival with decreasing socioeconomic status but mostly used only ecological measures of status and analytical methods estimating simple survival. This study investigate socio-economic differentials in cancer survival using four indicators of socioeconomic status; three individual and one ecological. It uses a relative survival method which gives a measure of excess mortality due to cancer. METHODS: This study uses prospective record linkage data from The Office for National Statistics Longitudinal Study for England and Wales. The participants are Longitudinal Study members, recorded at census in 1971 and 1981 and with a primary malignant cancer diagnosed at age 45 or above, between 1981 and 1997, with follow-up until end 2000. The outcome measure is relative survival/excess mortality, compared with age and sex adjusted survival of the general population. Relative survival and Poisson regression analyses are presented, giving models of relative excess mortality, adjusted for covariates. RESULTS: Different socioeconomic indicators detect survival differentials of varying magnitude and definition. For all cancers combined, the four indicators show similar effects. For individual cancers there are differences between indicators. Where there is an association, all indicators show poorer survival with lower socioeconomic status. CONCLUSION: Cancer survival differs markedly by socio-economic status. The commonly used ecological measure, the Carstairs Index, is adequate at demonstrating socioeconomic differentials in survival for combined cancers and some individual cancers. A combination of car access and housing tenure is more sensitive than the ecological Carstairs measure at detecting socioeconomic effects on survival – confirming Carstairs effects where they occur but additionally identifying effects for other cancers. Social class is a relatively weak indicator of survival differentials
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Detectable Clonal Mosaicism from Birth to Old Age and its Relationship to Cancer
Clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) was detected using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells (>5–10%) with the same abnormal karyotype (presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (<0.5%) from birth until 50 years of age, after which it rises rapidly to 2–3% in the elderly. Many of the mosaic anomalies are characteristic of those found in hematological cancers and identify common deleted regions that pinpoint the locations of genes previously associated with hematological cancers. Although only 3% of subjects with detectable clonal mosaicism had any record of hematological cancer prior to DNA sampling, those without a prior diagnosis have an estimated 10-fold higher risk of a subsequent hematological cancer (95% confidence interval = 6–18)
Introduction: Toward an Engaged Feminist Heritage Praxis
We advocate a feminist approach to archaeological heritage work in order to transform heritage practice and the production of archaeological knowledge. We use an engaged feminist standpoint and situate intersubjectivity and intersectionality as critical components of this practice. An engaged feminist approach to heritage work allows the discipline to consider women’s, men’s, and gender non-conforming persons’ positions in the field, to reveal their contributions, to develop critical pedagogical approaches, and to rethink forms of representation. Throughout, we emphasize the intellectual labor of women of color, queer and gender non-conforming persons, and early white feminists in archaeology
Genetic variation associated with circulating monocyte count in the eMERGE Network
With white blood cell count emerging as an important risk factor for chronic inflammatory diseases, genetic associations of differential leukocyte types, specifically monocyte count, are providing novel candidate genes and pathways to further investigate. Circulating monocytes play a critical role in vascular diseases such as in the formation of atherosclerotic plaque. We performed a joint and ancestry-stratified genome-wide association analyses to identify variants specifically associated with monocyte count in 11 014 subjects in the electronic Medical Records and Genomics Network. In the joint and European ancestry samples, we identified novel associations in the chromosome 16 interferon regulatory factor 8 (IRF8) gene (P-value = 2.78×10(−16), β = −0.22). Other monocyte associations include novel missense variants in the chemokine-binding protein 2 (CCBP2) gene (P-value = 1.88×10(−7), β = 0.30) and a region of replication found in ribophorin I (RPN1) (P-value = 2.63×10(−16), β = −0.23) on chromosome 3. The CCBP2 and RPN1 region is located near GATA binding protein2 gene that has been previously shown to be associated with coronary heart disease. On chromosome 9, we found a novel association in the prostaglandin reductase 1 gene (P-value = 2.29×10(−7), β = 0.16), which is downstream from lysophosphatidic acid receptor 1. This region has previously been shown to be associated with monocyte count. We also replicated monocyte associations of genome-wide significance (P-value = 5.68×10(−17), β = −0.23) at the integrin, alpha 4 gene on chromosome 2. The novel IRF8 results and further replications provide supporting evidence of genetic regions associated with monocyte count
Safety of procuring research tissue during a clinically indicated kidney biopsy from patients with lupus: data from the Accelerating Medicines Partnership RA/SLE Network
Objectives In lupus nephritis the pathological diagnosis from tissue retrieved during kidney biopsy drives treatment and management. Despite recent approval of new drugs, complete remission rates remain well under aspirational levels, necessitating identification of new therapeutic targets by greater dissection of the pathways to tissue inflammation and injury. This study assessed the safety of kidney biopsies in patients with SLE enrolled in the Accelerating Medicines Partnership, a consortium formed to molecularly deconstruct nephritis.Methods 475 patients with SLE across 15 clinical sites in the USA consented to obtain tissue for research purposes during a clinically indicated kidney biopsy. Adverse events (AEs) were documented for 30 days following the procedure and were determined to be related or unrelated by all site investigators. Serious AEs were defined according to the National Institutes of Health reporting guidelines.Results 34 patients (7.2%) experienced a procedure-related AE: 30 with haematoma, 2 with jets, 1 with pain and 1 with an arteriovenous fistula. Eighteen (3.8%) experienced a serious AE requiring hospitalisation; four patients (0.8%) required a blood transfusion related to the kidney biopsy. At one site where the number of cores retrieved during the biopsy was recorded, the mean was 3.4 for those who experienced a related AE (n=9) and 3.07 for those who did not experience any AE (n=140). All related AEs resolved.Conclusions Procurement of research tissue should be considered feasible, accompanied by a complication risk likely no greater than that incurred for standard clinical purposes. In the quest for targeted treatments personalised based on molecular findings, enhanced diagnostics beyond histology will likely be required
Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease
We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development
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