sleuth_alr_results: Return sleuth-ALR Results Table
In warrenmcg/sleuth-ALR: Compositional Approach to Sleuth Data Analysis

Description Usage Arguments Details Value

This is a wrapper function for sleuth_results that properly handles the unique features of sleuth-ALR-transformed data.

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sleuth_alr_results(obj, test, test_type = "wt", which_model = "full",
  show_all = TRUE, pval_aggregate = obj$pval_aggregate,
  weight_func = "best")

`obj`	a `sleuth` object
`test`	a character string denoting the test to extract. Possible tests can be found by using `models(obj)`.
`test_type`	'wt' for Wald test or 'lrt' for Likelihood Ratio test.
`which_model`	a character string denoting the model. If extracting a wald test, use the model name. Not used if extracting a likelihood ratio test.
`show_all`	if `TRUE` will show all transcripts (not only the ones passing filters). The transcripts that do not pass filters will have `NA` values in most columns.
`pval_aggregate`	if `TRUE` and both `target_mapping` and `aggregation_column` were provided, to `sleuth_prep`, use lancaster's method to aggregate p-values by the `aggregation_column`.
`weight_func`	if `pval_aggregate` is `TRUE`, then this is used to weight the p-values for lancaster's method. This must be either the string 'best' or it must be a function that takes the observed means of the transcripts as the only defined argument.

For the transcript-level analysis, this produces the same results as the default sleuth_results. However, using the default function for p-value aggregation is incompatible with the standard sleuth-ALR transformation. Sleuth-ALR logratios typically include negative values (any feature that is less abundant than the chosen 'reference feature(s)' will yield negative logratios), and negative values are not allowed for the lancaster method.

This method works around this problem by specifying a weighting function that is compatible with the logratios and with the lancaster method. The default is to specify the string 'best', which uses an internal function to determine how to exponentiate the logratios to get the ratios, using whatever base was used for the transformation.

a data.frame with the same specification as found in sleuth_results. See sleuth_results for details.

warrenmcg/sleuth-ALR documentation built on Oct. 27, 2020, 4:30 a.m.