Man pages for heiniglab/scPower
Experimental design framework for scRNAseq population studies (eQTL and DE)
| annot.df | Example annotation data frame matching the example count... |
| annot_smartseq | Example Smart-seq2 annotation data frame (matching the... |
| budgetCalculation | Calculate total cost dependent on parameters for 10X design |
| budgetCalculation.libPrepCell | Calculate total cost dependent on parameters for 10X design... |
| budgetCalculation.restrictedDoublets | Calculate total cost dependent on parameters (adaptation with... |
| budget.optimization | Optimal parameters for increasing budget and simulated and... |
| calculate.gene.counts | Get expressed genes from pseudobulk |
| calculate.probabilities | Help function to calculate expression probability, power and... |
| cellsBudgetCalculation | Estimate possible number of cells per individual depending on... |
| cellsBudgetCalculation.libPrepCell | Estimate possible number of cells per individual depending on... |
| cellsBudgetCalculation.restrictedDoublets | Estimate possible number of cells per individual depending on... |
| convert.gamma.parameters | Converts two different gamma parameterizations, one using... |
| count.matrix.example | Example count matrices to test the expression curve... |
| counts_smartseq | Example Smart-seq2 count matrix for the tutorial |
| create.pseudobulk | Reformat count matrix to 3D pseudocount matrix |
| de.ref.study | DE priors |
| dispersion.function.estimation | Get median values of parameters from the mean-dispersion fits... |
| disp.fun.param | Parameters for mean dispersion fit |
| disp.fun.param.drop | Parameters for mean dispersion fit - Drop-seq data |
| disp.fun.param.smart | Parameters for mean dispersion fit - Smart-seq2 data |
| effectSize.DE.simulation | Simulation of effect sizes for DE genes (FoldChanges) |
| effectSize.eQTL.simulation | Simulation of effect sizes for eQTL genes (FoldChanges) |
| eqtl.ref.study | eQTL priors |
| estimate.exp.prob.count.param | Estimate gene expression probability based on experimental... |
| estimate.exp.prob.param | Estimate gene expression probability based on experimental... |
| estimate.exp.prob.values | Estimate gene expression probability based on mean and... |
| estimate.mean.dsp.values | Get the mean and dispersion values for each genes |
| estimate.size.simulation | Estimation of size parameter (1/dsp) for eQTL power... |
| fdr.optimization | Function for numeric optimization to get an FDR corrected... |
| gamma.mixed.fits | Parameters for gamma umi fit |
| gamma.mixed.fits.drop | Parameters for gamma umi fit - Drop-seq |
| gamma.mixed.fits.smart | Parameters for gamma read fit - Smart-seq2 data |
| gene_length | Example gene length data frame |
| gene.rank.calculation | Calculation of gene ranks from a normalized count matrix |
| gene.rank.calculation.vector | Calculation of gene ranks using a vector of mean expression... |
| meanUMI.calculation | Calculate the mean UMI count per cell |
| mixed.gamma.estimation | Estimate the mixed gamma distribution of the mean values |
| nbinom.estimation | Estimate the mean and dispersion parameter for each gene |
| number.cells.detect.celltype | Cell sample size calculation for cell type identification |
| observed.gene.counts | Observed gene counts from multiple data sets to reproduce... |
| optimize.constant.budget | Optimizing cost parameters to maximize detection power for a... |
| optimize.constant.budget.libPrepCell | Optimizing cost parameters to maximize detection power for a... |
| optimize.constant.budget.restrictedDoublets | Optimizing cost parameters to maximize detection power for a... |
| optimize.constant.budget.smartseq | Optimizing cost parameters to maximize detection power for a... |
| optimizeSizeFactor | Function for numeric optimization of size parameter |
| parametricDispersionFit_DEseq | Reimplementation of DEseq function for fitting... |
| power.de | Power calculation for a DE gene |
| power.detect.celltype | Power calculation for cell type identification |
| power.eqtl | Wrapper funtion to use either simulated power or power based... |
| power.eqtl.ftest | Power calculation for an eQTL gene using the F-test |
| power.eqtl.simulated | Power calculation for an eQTL gene using simulations |
| power.eqtl.simulated.help | Helper function for eQTL simulation power calculation |
| power.general.restrictedDoublets | Power calculation for a DE/eQTL study with 10X design (with a... |
| power.general.withDoublets | Power calculation for a DE/eQTL study with 10X design (with a... |
| power.sameReadDepth.restrictedDoublets | Power calculation for a DE/eQTL study with same read depth as... |
| power.sameReadDepth.withDoublets | Power calculation for a DE/eQTL study with same read depth as... |
| power.smartseq | Power calculation for a DE/eQTL study with Smart-seq design |
| print_optimalDesign_10X | Print design parameters of optimal design |
| readDepthBudgetCalculation | Estimate possible read depth depending on the total cost and... |
| readDepthBudgetCalculation.libPrepCell | Estimate possible read depth depending on the total cost,... |
| readDepthBudgetCalculation.restrictedDoublets | Estimate possible read depth depending on the total cost and... |
| read.umi.fit | Parameters for read umi fit |
| runShiny | Run Shiny app for power estimation |
| sample.disp.values | Sample the dispersion values dependent on mean values using... |
| sample.mean.values.quantiles | Draw the mean values using the quantile distributions of the... |
| sample.mean.values.random | Randomly sample the mean values using the gamma mixed... |
| sampleSizeBudgetCalculation | Estimate possible sample size depending on the total cost and... |
| sampleSizeBudgetCalculation.libPrepCell | Estimate possible sample size depending on the total cost,... |
| sampleSizeBudgetCalculation.restrictedDoublets | Estimate possible sample size depending on the total cost and... |
| select.cutoffs | Identifying the expression threshold combination that... |
| sim.eqtl.pvals | Precalcuated p-values from eQTL simulation |
| simulated.DE.values | Results of DE power generated by simulations with powsimR |
| simulated.eQTL.values | Results of eQTL power generated by self-implemented... |
| size.estimates | Precalcuated size estimates for eQTL power simulation |
| sizeFactorsPosCounts | Reimplementation of DEseq2 function for size factors with... |
| sizeFactorsStandard | Reimplementation of DEseq function for size factors |
| umi.gamma.relation | Estimate linear relationship between the gamma mixed... |
| umi.read.relation | Estimate logarithmic relationship between mean UMI counts and... |
| uniform.ranks.interval | Simulation of gene ranks uniformly distributed in a certain... |
| visualize.gamma.fits | Plotting function to visualize simulated mean values from... |
| visualize.power.grid | Plotting function to visualize calculated power as heatmap,... |
