This function extracts Wald test results from a sleuth object.
sleuth_results(obj, test, test_type = "wt", which_model = "full",
rename_cols = TRUE, show_all = TRUE)a sleuth object
a character string denoting the test to extract. Possible tests can be found by using models(obj).
a character string denoting the model. If extracting a wald test, use the model name. If extracting a likelihood ratio test, use 'lrt'.
if TRUE will rename some columns to be shorter and
consistent with vignette
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)
# NOT RUN {
models(sleuth_obj) # for this example, assume the formula is ~condition,
and a coefficient is IP
results_table <- sleuth_results(sleuth_obj, 'conditionIP')
# }
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