Function reference • isotwas

Training models

Functions for training multivariate predictive models

compute_isotwas(): Compute isoTWAS model for a set of isoforms/transcripts

curds_whey(): Breiman and Friedman's curds and whey multivariate regression

compute_curds_whey(): Breiman and Friedman's curds and whey multivariate regression with CV

finemap_regress(): Fine-mapping and clustering SEs with SUR

compute_finemap_regress(): Fine-mapping and clustering SEs with SUR

compute_fixed(): Multivariate regression with covariance estimate

compute_mrce(): Multivariate regression with covariance estimate

compute_omega(): Compute precision matrix between isoforms

compute_blup(): Univariate BLUP on all columns

multivariate_elasticnet(): Multivariate elastic net on all columns with row-wise penalty

multivariate_joinet(): Multivariate stacked elastic net on all columns using joinet

multivariate_spls(): Multivariate sparse partial least squares

univariate_blup(): Univariate BLUP on all columns

univariate_elasticnet(): Univariate elastic net on all columns

univariate_susie(): Univariate SuSiE on all columns

convert_model(): Convert isotwas model list to tibble

Trait mapping

Stage-wise trait mapping

p_screen(): Compute screening P-value for one gene

p_confirm(): Compute confirmation P-value for one gene

burdenTest(): Compute weighted burden test

Probabilistic fine-mapping

Functions for FOCUS-like probabilistic fine-mapping

twas_finemap(): FOCUS-like gene-level finemapping

estimate_cor(): Compute correlation for fine-mapping

get_resid(): Compute residuals for Z-scores

bayes_factor(): Compute Bayes factors for TWAS Z-scores

conditional_test_focus(): Conditional gene-level test

conditional_test(): Conditional gene-level test