sleuth_results: Extract Wald test results from a sleuth object
In pachterlab/zika: Tools for investigating RNA-Seq

Description Usage Arguments Value See Also Examples

This function extracts Wald test results from a sleuth object.

1 2	sleuth_results(obj, test, test_type = "wt", which_model = "full", rename_cols = TRUE, show_all = TRUE)

`obj`	a `sleuth` object
`test`	a character string denoting the test to extract. Possible tests can be found by using `models(obj)`.
`which_model`	a character string denoting the model. If extracting a wald test, use the model name. If extracting a likelihood ratio test, use 'lrt'.
`rename_cols`	if `TRUE` will rename some columns to be shorter and consistent with vignette
`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.

a data.frame with the following columns:

target_id: transcript name, e.g. "ENSXX#####" (dependent on the transcriptome used in kallisto)

pval: p-value of the chosen model

qval: false discovery rate adjusted p-value, using Benjamini-Hochberg (see p.adjust)

b: 'beta' value (effect size). Technically a biased estimator of the fold change

se_b: standard error of the beta

mean_obs: mean of natural log counts of observations

var_obs: variance of observation

tech_var: technical variance of observation from the bootstraps

sigma_sq: raw estimator of the variance once the technical variance has been removed

smooth_sigma_sq: smooth regression fit for the shrinkage estimation

final_simga_sq: max(sigma_sq, smooth_sigma_sq); used for covariance estimation of beta

sleuth_wt and sleuth_lrt to compute tests, models to view which models, tests to view which tests were performed (and can be extracted)

1
2
3

models(sleuth_obj) # for this example, assume the formula is ~condition,
                     and a coefficient is IP
results_table <- sleuth_results(sleuth_obj, 'conditionIP')