We are analyzing https://link.springer.com/article/10.1186/s13059-015-0844-5.

Title:
MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data | Genome Biology
Description:
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 .
Website Age:
28 years and 1 months (reg. 1997-05-29).

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Keywords {🔍}

cells, expression, genes, gene, cdr, data, cell, model, pubmed, analysis, article, additional, singlecell, file, mast, scholar, modules, google, mait, figure, treatment, set, methods, expressed, approach, stimulation, cas, continuous, fig, stimulated, module, residuals, component, central, enrichment, shalek, rate, discrete, nonstimulated, observed, cellular, rnaseq, control, gsea, biological, variance, response, linear, experiments, effects,

Topics {✒️}

=\frac{\widehat{\theta}-{\widehat{\theta}}_0}{\sqrt{\widehat{var}\left single-cell rna-seq data live cd3+cd8+ cd4-cd161hivα7 single-cell rna-seq experiments single-cell expression profiles single-cell sequencing identifies rna-seq read counts single-cell rna-seq article download pdf martin prlic single-cell sequencing data future single-cell studies repeated single-cell measurements bulk rna-seq data �t-cell surface signature” raphael gottardo mountain view single-cell expression data gene set-based statistics single-cell residuals produced /rglab/mastdata/archive/v1 shrunken gene-specific precision powerful multi-parametric measurements =1}^{g_0}{\widehat{\beta}}_g} scrna-seq data sets gene-specific inverse variances bystander-activated memory cd8 empirical bayes method transcriptional profile precedes subsequent protein-level single-cell transcriptomics helps improve inference 5em {\displaystyle {\sum}_{ +2{\displaystyle {\sum}_{1\le t-cell signaling module single-cell module scores post-sort experiments transcriptome expression profiling rna-seq experiment myeloid dendritic cells single-read sequencing gene-specific variance estimates rna-seq data accurate transcript quantification providing 2α pseudo-observations bulk rna-seq natural killer t-cells combined z-score summarizes open software development {\widehat{\theta}}_0

Questions {❓}

The question is essentially ontological: is the CDR a mediator of the treatment effect (is it caused by the treatment and intermediate to expression of the gene of interest), or does it confound the treatment effect (does it happen to co-occur with treatment)?

Schema {🗺️}

WebPage:
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         description: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 .
         datePublished:2015-12-10T00:00:00Z
         dateModified:2015-12-10T00:00:00Z
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            Bimodality
            Cellular detection rate
            Co-expression
            Empirical Bayes
            Generalized linear model
            Gene set enrichment analysis
            Animal Genetics and Genomics
            Human Genetics
            Plant Genetics and Genomics
            Microbial Genetics and Genomics
            Bioinformatics
            Evolutionary Biology
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      headline:MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data
      description: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 .
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      dateModified:2015-12-10T00:00:00Z
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         Bimodality
         Cellular detection rate
         Co-expression
         Empirical Bayes
         Generalized linear model
         Gene set enrichment analysis
         Animal Genetics and Genomics
         Human Genetics
         Plant Genetics and Genomics
         Microbial Genetics and Genomics
         Bioinformatics
         Evolutionary Biology
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                  address:
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                     type:PostalAddress
                  type:Organization
            type:Person
            name:Andrew McDavid
            affiliation:
                  name:Fred Hutchinson Cancer Research Center
                  address:
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                     type:PostalAddress
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            affiliation:
                  name:Fred Hutchinson Cancer Research Center
                  address:
                     name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Jingyuan Deng
            affiliation:
                  name:Fred Hutchinson Cancer Research Center
                  address:
                     name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Vivian Gersuk
            affiliation:
                  name:Benaroya Research Institute at Virginia Mason
                  address:
                     name:Benaroya Research Institute at Virginia Mason, Seattle, USA
                     type:PostalAddress
                  type:Organization
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                  name:MIT
                  address:
                     name:Institute for Medical Engineering & Science, MIT, Boston, USA
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                     type:PostalAddress
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            type:Person
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                  address:
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                     type:PostalAddress
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                  address:
                     name:Benaroya Research Institute at Virginia Mason, Seattle, USA
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            type:Person
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Person:
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            address:
               name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
               type:PostalAddress
            type:Organization
      name:Andrew McDavid
      affiliation:
            name:Fred Hutchinson Cancer Research Center
            address:
               name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
               type:PostalAddress
            type:Organization
      name:Masanao Yajima
      affiliation:
            name:Fred Hutchinson Cancer Research Center
            address:
               name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
               type:PostalAddress
            type:Organization
      name:Jingyuan Deng
      affiliation:
            name:Fred Hutchinson Cancer Research Center
            address:
               name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
               type:PostalAddress
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      name:Vivian Gersuk
      affiliation:
            name:Benaroya Research Institute at Virginia Mason
            address:
               name:Benaroya Research Institute at Virginia Mason, Seattle, USA
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      name:Alex K. Shalek
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            name:MIT
            address:
               name:Institute for Medical Engineering & Science, MIT, Boston, USA
               type:PostalAddress
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            address:
               name:Department of Chemistry, MIT, Boston, USA
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               name:Ragon Institute of MGH, MIT, & Harvard, Boston, USA
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            address:
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               type:PostalAddress
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      name:Martin Prlic
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               name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
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            address:
               name:Benaroya Research Institute at Virginia Mason, Seattle, USA
               type:PostalAddress
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      name:Raphael Gottardo
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PostalAddress:
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      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Benaroya Research Institute at Virginia Mason, Seattle, USA
      name:Institute for Medical Engineering & Science, MIT, Boston, USA
      name:Department of Chemistry, MIT, Boston, USA
      name:Ragon Institute of MGH, MIT, & Harvard, Boston, USA
      name:Broad Institute of MIT & Harvard, Boston, USA
      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Benaroya Research Institute at Virginia Mason, Seattle, USA
      name:Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA
      name:Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, USA

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