From cf1fac3baa250746a7482406178da9a62f4174d0 Mon Sep 17 00:00:00 2001 From: stemangiola Date: Wed, 21 Dec 2022 16:20:53 +1100 Subject: [PATCH] update README --- README.md | 64 +++++++++++++++------------- inst/figures/unnamed-chunk-12-1.png | Bin 63668 -> 62730 bytes inst/figures/unnamed-chunk-13-1.png | Bin 52033 -> 51258 bytes inst/figures/unnamed-chunk-14-1.png | Bin 43602 -> 45763 bytes inst/figures/unnamed-chunk-15-1.png | Bin 52033 -> 51258 bytes inst/figures/unnamed-chunk-16-1.png | Bin 25897 -> 26327 bytes man/fragments/intro.Rmd | 2 +- 7 files changed, 35 insertions(+), 31 deletions(-) diff --git a/README.md b/README.md index 5a457249..c43b9a70 100644 --- a/README.md +++ b/README.md @@ -81,16 +81,16 @@ counts_obj |> ## # A tibble: 72 × 18 ## cell_group parameter factor c_lower c_eff…¹ c_upper c_pH0 c_FDR c_n_eff ## - ## 1 B1 (Intercept) 0.869 1.06 1.24 0 0 4529. - ## 2 B1 typecancer type -1.21 -0.878 -0.538 0 0 4296. - ## 3 B2 (Intercept) 0.423 0.697 0.959 5.00e-4 3.75e-5 3358. - ## 4 B2 typecancer type -1.21 -0.784 -0.363 3.75e-3 6.11e-4 4084. - ## 5 B3 (Intercept) -0.643 -0.383 -0.136 7.17e-2 4.01e-3 5204. - ## 6 B3 typecancer type -0.616 -0.224 0.137 4.54e-1 1.37e-1 4037. - ## 7 BM (Intercept) -1.27 -1.02 -0.754 0 0 5698. - ## 8 BM typecancer type -0.764 -0.347 0.0320 2.24e-1 3.62e-2 4352. - ## 9 CD4 1 (Intercept) 0.121 0.324 0.522 1.03e-1 1.15e-2 3652. - ## 10 CD4 1 typecancer type -0.110 0.157 0.425 6.36e-1 2.19e-1 2916. + ## 1 B1 (Intercept) 0.873 1.06 1.23 0 0 4746. + ## 2 B1 typecancer type -1.23 -0.878 -0.527 2.50e-4 6.25e-5 2626. + ## 3 B2 (Intercept) 0.415 0.691 0.950 7.50e-4 6.25e-5 5154. + ## 4 B2 typecancer type -1.21 -0.772 -0.351 5.50e-3 8.33e-4 4362. + ## 5 B3 (Intercept) -0.632 -0.387 -0.152 6.07e-2 3.38e-3 4135. + ## 6 B3 typecancer type -0.605 -0.225 0.142 4.47e-1 1.39e-1 3179. + ## 7 BM (Intercept) -1.29 -1.02 -0.750 0 0 4836. + ## 8 BM typecancer type -0.756 -0.346 0.0353 2.35e-1 5.7 e-2 3588. + ## 9 CD4 1 (Intercept) 0.116 0.322 0.509 1.12e-1 1.15e-2 3516. + ## 10 CD4 1 typecancer type -0.103 0.164 0.435 6.04e-1 2.20e-1 2549. ## # … with 62 more rows, 9 more variables: c_R_k_hat , v_lower , ## # v_effect , v_upper , v_pH0 , v_FDR , v_n_eff , ## # v_R_k_hat , count_data , and abbreviated variable name ¹​c_effect @@ -116,16 +116,16 @@ seurat_obj |> ## # A tibble: 60 × 18 ## cell_group param…¹ factor c_lower c_eff…² c_upper c_pH0 c_FDR c_n_eff ## - ## 1 B immature typeca… type -2.01 -1.57 -1.12 0 0 NA - ## 2 B immature typehe… type 1.12 1.57 2.01 0 0 NA - ## 3 B mem typeca… type -2.31 -1.71 -1.11 0 0 NA - ## 4 B mem typehe… type 1.11 1.71 2.31 0 0 NA - ## 5 CD4 cm high c… typeca… type 0.940 1.86 3.00 0 0 NA - ## 6 CD4 cm high c… typehe… type -3.00 -1.86 -0.940 0 0 NA - ## 7 CD4 cm riboso… typeca… type 0.571 1.24 1.97 1.50e-3 3.89e-4 NA - ## 8 CD4 cm riboso… typehe… type -1.97 -1.24 -0.571 1.50e-3 3.89e-4 NA - ## 9 CD4 cm S100A4 typeca… type -1.24 -0.882 -0.540 2.50e-4 5.00e-5 NA - ## 10 CD4 cm S100A4 typehe… type 0.540 0.882 1.24 2.50e-4 5.00e-5 NA + ## 1 B immature typeca… type -2.03 -1.58 -1.12 0 0 NA + ## 2 B immature typehe… type 1.12 1.58 2.03 0 0 NA + ## 3 B mem typeca… type -2.51 -1.93 -1.34 0 0 NA + ## 4 B mem typehe… type 1.34 1.93 2.51 0 0 NA + ## 5 CD4 cm high c… typeca… type 0.952 1.86 2.93 2.50e-4 5.00e-5 NA + ## 6 CD4 cm high c… typehe… type -2.93 -1.86 -0.952 2.50e-4 5.00e-5 NA + ## 7 CD4 cm riboso… typeca… type 0.553 1.25 2.00 1.00e-3 2.81e-4 NA + ## 8 CD4 cm riboso… typehe… type -2.00 -1.25 -0.553 1.00e-3 2.81e-4 NA + ## 9 CD4 cm S100A4 typeca… type -1.27 -0.886 -0.540 0 0 NA + ## 10 CD4 cm S100A4 typehe… type 0.540 0.886 1.27 0 0 NA ## # … with 50 more rows, 9 more variables: c_R_k_hat , v_lower , ## # v_effect , v_upper , v_pH0 , v_FDR , v_n_eff , ## # v_R_k_hat , count_data , and abbreviated variable names @@ -182,6 +182,10 @@ loo_compare( ) ``` + ## elpd_diff se_diff + ## model1 0.0 0.0 + ## model2 -79.9 11.3 + ## Differential variability, binary factor We can model the cell-group variability also dependent on the type, and @@ -205,16 +209,16 @@ res ## # A tibble: 60 × 18 ## cell_group param…¹ factor c_lower c_eff…² c_upper c_pH0 c_FDR c_n_eff ## - ## 1 B immature (Inter… 0.582 0.965 1.33 5.00e-4 5.36e-5 5635. - ## 2 B immature typehe… type 0.967 1.49 2.00 0 0 3507. - ## 3 B mem (Inter… -1.65 -1.08 -0.467 3.00e-3 4.03e-4 3873. - ## 4 B mem typehe… type 1.24 2.00 2.75 2.50e-4 8.33e-5 3301. - ## 5 CD4 cm high c… (Inter… -0.831 -0.390 0.103 2.08e-1 3.12e-2 4146. - ## 6 CD4 cm high c… typehe… type -3.19 -1.39 1.51 1.86e-1 4.81e-2 2131. - ## 7 CD4 cm riboso… (Inter… 0.166 0.491 0.850 4.10e-2 2.82e-3 3992. - ## 8 CD4 cm riboso… typehe… type -2.45 -1.74 -0.841 2.25e-3 6.25e-4 4160. - ## 9 CD4 cm S100A4 (Inter… 1.76 2.01 2.26 0 0 6267. - ## 10 CD4 cm S100A4 typehe… type 0.337 0.743 1.16 2.50e-3 1.00e-3 3289. + ## 1 B immature (Inter… 0.599 0.967 1.33 2.50e-4 1.92e-5 5475. + ## 2 B immature typehe… type 0.972 1.48 2.01 0 0 3797. + ## 3 B mem (Inter… -1.65 -1.08 -0.485 3.00e-3 2.50e-4 3272. + ## 4 B mem typehe… type 1.29 1.99 2.76 0 0 2681. + ## 5 CD4 cm high c… (Inter… -0.829 -0.389 0.107 2.07e-1 2.40e-2 4299. + ## 6 CD4 cm high c… typehe… type -3.24 -1.39 1.47 1.98e-1 4.96e-2 2844. + ## 7 CD4 cm riboso… (Inter… 0.158 0.499 0.857 4.00e-2 2.76e-3 3827. + ## 8 CD4 cm riboso… typehe… type -2.47 -1.75 -0.825 1.75e-3 6.00e-4 2875. + ## 9 CD4 cm S100A4 (Inter… 1.76 2.01 2.26 0 0 6613. + ## 10 CD4 cm S100A4 typehe… type 0.364 0.739 1.15 2.50e-3 9.17e-4 4323. ## # … with 50 more rows, 9 more variables: c_R_k_hat , v_lower , ## # v_effect , v_upper , v_pH0 , v_FDR , v_n_eff , ## # v_R_k_hat , count_data , and abbreviated variable names diff --git a/inst/figures/unnamed-chunk-12-1.png b/inst/figures/unnamed-chunk-12-1.png index 64ccfbcdda4c3146f224a3146cd7798905062b25..ac2b27d068b80865fffc8825df0dbe41f6bc2293 100644 GIT binary patch literal 62730 zcmcfpbyQYu)IAE{pdf;TNFyO2AdNKA4N7-Qmw*CNQi2E)64FS6bax9#cbAl;NJ}Gd 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In this case, -79.9 / 11.5 = -6.9, therefore we can conclude that model one, the one with factor association, is better than model two. -```{r, eval=FALSE, message=FALSE, warning=FALSE} +```{r, message=FALSE, warning=FALSE} library(loo) # Fit first model