An example of count data for an experiment without spike-ins

pulseRFractionData

Format

A list containing simulated data, model and parameter information.

  • formulas describe the model for mean read number

  • counts contain the simulated data

  • conditions is a data.frame describing sample time point and type

  • fractions is a character vector to divide samples into groups for normalisation

  • formulaIndexes is a list of formula names (see formulas), which are used in linear combination with coefficients in normFactors to calculate mean read number

  • normFactors are coefficients which relate quantities of RNA between different groups and can be used as normalisation coefficients for calculation of mean read numbers using formulas and formulaIndexes

  • par is a list of model parameters

Details

The data set contains simulation of an experiment which measures three fractions, namely, coded as 'A_fraction', 'B_fraction' and 'C_fraction'. There are three types of quantities, 'A', 'B' and 'C' for which a kinetic model is defined, see formulas element in the data set:

(A = a * p, B = a * b^time, C = a * (1 - b^time)),

where a, b are gene-specific parameters which are unknown, p is a vector of known gene-specific parameters (e.g. probability of capture depending on the uridine content etc.)

The data are generated for 3 replicates, 3 different time points and for 10 different genes, see elements counts and conditions.

The model considers possibility of cross-contamination with different types of RNA, which is described by formulaIndexes. In this case, the mean read number for a gene is a linear combination of the described RNA types with weights defined in normFactors.

Due to different amounts of RNA in different conditions, the normalisation factors are defined for groups of the samples, hence they are shared values for a given sample group. The grouping is defined by groups element of the data set.

The true parameter values, which are used for data simulation are in par element. This also includes the size parameter for the negative binomial distribution.