Stefano Mangiola
devtools::install_github("stemangiola/ARMET")library(ARMET)## Loading required package: Rcpp
## Warning: replacing previous import 'tidyr::extract' by 'rstan::extract' when
## loading 'ARMET'
library(dplyr)##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
data("test_mixture")
data("no_hierarchy_reference")
estimates =
test_mixture |>
convoluted_glm(
~ factor_of_interest,
.sample = sample,
.transcript = symbol,
.abundance = count,
reference = no_hierarchy_reference
)## Warning in setup_convolved_lm_NON_hierarchical(.data, .formula = .formula, :
## tidybulk says: the data does not have the same number of transcript per sample.
## The data set is not rectangular.
## Warning in aggregate_duplicated_transcripts_bulk(.data, .sample = !!.sample, :
## tidybulk says: for aggregation, factors and logical columns were converted to
## character
## Converted to characters
## factorfactorlogical
## Warning in warning_if_data_is_not_rectangular(.data, !!.sample, !!.transcript, :
## tidybulk says: the data does not have the same number of transcript per sample.
## The data set is not rectangular.
## No group or design set. Assuming all samples belong to one group.
## Warning in warning_if_data_is_not_rectangular(.data, !!.sample, !!.transcript, :
## tidybulk says: the data does not have the same number of transcript per sample.
## The data set is not rectangular.
## Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
## Running the chains for more iterations may help. See
## https://mc-stan.org/misc/warnings.html#bulk-ess
## Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
## Running the chains for more iterations may help. See
## https://mc-stan.org/misc/warnings.html#tail-ess
## # A tibble: 0 × 11
## # … with 11 variables: par <chr>, mean <dbl>, se_mean <dbl>, sd <dbl>,
## # 2.5% <dbl>, 25% <dbl>, 50% <dbl>, 75% <dbl>, 97.5% <dbl>, n_eff <dbl>,
## # Rhat <dbl>
## Warning: Expected 5 pieces. Additional pieces discarded in 126 rows [1, 2, 3, 4,
## 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
## Warning: Expected 5 pieces. Additional pieces discarded in 126 rows [1, 2, 3, 4,
## 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
## Joining, by = c("Q", "sample")
## Warning: Expected 5 pieces. Additional pieces discarded in 246 rows [1, 2, 3, 4,
## 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
## Warning: Expected 5 pieces. Additional pieces discarded in 42 rows [1, 2, 3, 4,
## 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
## Warning in mask$eval_all_mutate(quo): NAs introduced by coercion
## Warning: Expected 5 pieces. Additional pieces discarded in 42 rows [1, 2, 3, 4,
## 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
## Warning in mask$eval_all_mutate(quo): NAs introduced by coercion
estimates## # A tibble: 21 × 5
## cell_type `.median_(Inte…` .median_factor_… `.sd_(Intercep…` .sd_factor_of_i…
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 endothel… -0.717 -0.248 0.406 0.456
## 2 epitheli… -0.582 -0.313 0.418 0.480
## 3 fibrobla… -0.677 -0.292 0.458 0.486
## 4 mast_cell -0.804 -0.299 0.485 0.444
## 5 b_memory 2.04 2.30 0.396 0.397
## 6 b_naive 5.93 -0.215 0.230 0.296
## 7 eosinoph… 0.284 0.705 0.486 0.504
## 8 monocyte -0.321 -0.0574 0.447 0.482
## 9 neutroph… -0.165 0.130 0.482 0.556
## 10 nk_resti… -0.391 -0.0737 0.431 0.486
## # … with 11 more rows