sleuth_fit: Fit a measurement error model
In pachterlab/zika: Tools for investigating RNA-Seq

Description Usage Arguments Details Value See Also Examples

This function is a wrapper for fitting a measurement error model using sleuth. It performs the technical variance estimation from the boostraps, biological variance estimation, and shrinkage estimation.

1	sleuth_fit(obj, formula = NULL, fit_name = NULL, ...)

`obj`	a `sleuth` object
`formula`	an R formula specifying the design to fit OR a design matrix. If you are interested in only fitting the model that was specified in `sleuth_prep` you do not need to specify it again (will be fit as the 'full' model).
`fit_name`	the name to store the fit in the sleuth object (at so$fits$fit_name). If `NULL`, the model will be named 'full'.
`...`	additional arguments passed to `sliding_window_grouping` and `shrink_df`

For most users, simply providing the sleuth object should be sufficient. By default, this behavior will fit the full model initially specified and store it in the sleuth object under 'full'.

To see which models have been fit, users will likely find the function models helpful.

a sleuth object with updated attributes.

models for seeing which models have been fit, sleuth_prep for creating a sleuth object, sleuth_wt to test whether a coefficient is zero, sleuth_lrt to test nested models.

# If you specified the formula in sleuth_prep, you can simply run to run the full model
so <- sleuth_fit(so)
# The intercept only model can be fit like this
so <- sleuth_fit(so, ~1, 'reduced')