Last updated: 2024-07-26

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File Version Author Date Message
html 7a9f863 Evgenii O. Tretiakov 2024-07-26 Build site.
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Rmd d09b2f1 EugOT 2024-03-20 calculate cell viability MTT assay 
df <- read_tsv(here(data_dir, "ASTRO_MTT_EPA.tsv"))
df <- df %>%
  tidyr::gather(key = Group, value = Measurement)

kable(df)
Group Measurement
Ctr_1 0.647
Ctr_1 0.657
Ctr_1 0.580
Ctr_1 0.622
Ctr_1 0.644
Ctr_1 0.589
Ctr_1 0.604
Ctr_1 0.561
EPA_5μM_1 0.638
EPA_5μM_1 0.643
EPA_5μM_1 0.667
EPA_5μM_1 0.680
EPA_5μM_1 0.630
EPA_5μM_1 0.658
EPA_5μM_1 0.627
EPA_5μM_1 0.649
EPA_10μM_1 0.630
EPA_10μM_1 0.651
EPA_10μM_1 0.669
EPA_10μM_1 0.670
EPA_10μM_1 0.677
EPA_10μM_1 0.670
EPA_10μM_1 0.737
EPA_10μM_1 0.683
EPA_30μM_1 0.731
EPA_30μM_1 0.733
EPA_30μM_1 0.797
EPA_30μM_1 0.758
EPA_30μM_1 0.737
EPA_30μM_1 0.735
EPA_30μM_1 0.510
EPA_30μM_1 0.673
Ctr_2 0.830
Ctr_2 0.847
Ctr_2 0.824
Ctr_2 0.832
Ctr_2 0.900
Ctr_2 0.877
Ctr_2 0.857
Ctr_2 0.767
EPA_5μM_2 0.859
EPA_5μM_2 0.914
EPA_5μM_2 0.928
EPA_5μM_2 0.941
EPA_5μM_2 0.888
EPA_5μM_2 0.907
EPA_5μM_2 0.988
EPA_5μM_2 0.857
EPA_10μM_2 0.850
EPA_10μM_2 0.893
EPA_10μM_2 0.880
EPA_10μM_2 0.934
EPA_10μM_2 0.943
EPA_10μM_2 0.909
EPA_10μM_2 0.898
EPA_10μM_2 0.931
EPA_30μM_2 0.896
EPA_30μM_2 0.975
EPA_30μM_2 0.919
EPA_30μM_2 0.966
EPA_30μM_2 0.952
EPA_30μM_2 0.977
EPA_30μM_2 0.974
EPA_30μM_2 0.872
Ctr_3 0.731
Ctr_3 0.745
Ctr_3 0.705
Ctr_3 0.692
Ctr_3 0.748
Ctr_3 0.744
Ctr_3 0.771
Ctr_3 0.661
EPA_5μM_3 0.726
EPA_5μM_3 0.770
EPA_5μM_3 0.754
EPA_5μM_3 0.725
EPA_5μM_3 0.688
EPA_5μM_3 0.768
EPA_5μM_3 0.753
EPA_5μM_3 0.708
EPA_10μM_3 0.753
EPA_10μM_3 0.787
EPA_10μM_3 0.782
EPA_10μM_3 0.744
EPA_10μM_3 0.747
EPA_10μM_3 0.788
EPA_10μM_3 0.748
EPA_10μM_3 0.729
EPA_30μM_3 0.759
EPA_30μM_3 0.809
EPA_30μM_3 0.790
EPA_30μM_3 0.855
EPA_30μM_3 0.797
EPA_30μM_3 0.845
EPA_30μM_3 0.842
EPA_30μM_3 0.824
Ctr_4 0.840
Ctr_4 0.754
Ctr_4 0.744
Ctr_4 0.798
Ctr_4 0.788
Ctr_4 0.810
Ctr_4 0.820
Ctr_4 0.825
EPA_5μM_4 0.778
EPA_5μM_4 0.803
EPA_5μM_4 0.791
EPA_5μM_4 0.761
EPA_5μM_4 0.760
EPA_5μM_4 0.750
EPA_5μM_4 0.765
EPA_5μM_4 0.765
EPA_10μM_4 0.790
EPA_10μM_4 0.763
EPA_10μM_4 0.833
EPA_10μM_4 0.806
EPA_10μM_4 0.787
EPA_10μM_4 0.785
EPA_10μM_4 0.790
EPA_10μM_4 0.839
EPA_30μM_4 0.859
EPA_30μM_4 0.859
EPA_30μM_4 0.881
EPA_30μM_4 0.887
EPA_30μM_4 0.911
EPA_30μM_4 0.839
EPA_30μM_4 0.916
EPA_30μM_4 0.920
Ctr_5 0.571
Ctr_5 0.541
Ctr_5 0.539
Ctr_5 0.529
Ctr_5 0.509
Ctr_5 0.568
Ctr_5 0.504
Ctr_5 0.516
EPA_5μM_5 0.531
EPA_5μM_5 0.529
EPA_5μM_5 0.510
EPA_5μM_5 0.531
EPA_5μM_5 0.531
EPA_5μM_5 0.528
EPA_5μM_5 0.506
EPA_5μM_5 0.519
EPA_10μM_5 0.529
EPA_10μM_5 0.551
EPA_10μM_5 0.552
EPA_10μM_5 0.535
EPA_10μM_5 0.545
EPA_10μM_5 0.545
EPA_10μM_5 0.515
EPA_10μM_5 0.540
EPA_30μM_5 0.611
EPA_30μM_5 0.621
EPA_30μM_5 0.706
EPA_30μM_5 0.577
EPA_30μM_5 0.579
EPA_30μM_5 0.590
EPA_30μM_5 0.560
EPA_30μM_5 0.588
Ctr_6 0.510
Ctr_6 0.520
Ctr_6 0.560
Ctr_6 0.540
Ctr_6 0.520
Ctr_6 0.580
Ctr_6 0.550
Ctr_6 0.510
EPA_5μM_6 0.580
EPA_5μM_6 0.620
EPA_5μM_6 0.710
EPA_5μM_6 0.630
EPA_5μM_6 0.620
EPA_5μM_6 0.620
EPA_5μM_6 0.640
EPA_5μM_6 0.600
EPA_10μM_6 0.570
EPA_10μM_6 0.590
EPA_10μM_6 0.610
EPA_10μM_6 0.560
EPA_10μM_6 0.610
EPA_10μM_6 0.560
EPA_10μM_6 0.580
EPA_10μM_6 0.570
EPA_30μM_6 0.680
EPA_30μM_6 0.670
EPA_30μM_6 0.650
EPA_30μM_6 0.650
EPA_30μM_6 0.650
EPA_30μM_6 0.680
EPA_30μM_6 0.680
EPA_30μM_6 0.660

5 μM of EPA

unpaired5 <- load(df,
  x = Group, y = Measurement,
  idx = list(
    c("Ctr_1", "EPA_5μM_1"),
    c("Ctr_2", "EPA_5μM_2"),
    c("Ctr_3", "EPA_5μM_3"),
    c("Ctr_4", "EPA_5μM_4"),
    c("Ctr_5", "EPA_5μM_5"),
    c("Ctr_6", "EPA_5μM_6")
  ),
  minimeta = TRUE
)
print(unpaired5)
DABESTR v2023.9.12
==================

Good morning!
The current time is 09:51 AM on Friday July 26, 2024.

Effect size(s) with 95% confidence intervals will be computed for:
1. EPA_5μM_1 minus Ctr_1
2. EPA_5μM_2 minus Ctr_2
3. EPA_5μM_3 minus Ctr_3
4. EPA_5μM_4 minus Ctr_4
5. EPA_5μM_5 minus Ctr_5
6. EPA_5μM_6 minus Ctr_6
7. weighted delta (only for mean difference)

5000 resamples will be used to generate the effect size bootstraps.
unpaired5.mean_diff <- mean_diff(unpaired5)

print(unpaired5.mean_diff)
DABESTR v2023.9.12
==================

Good morning!
The current time is 09:51 AM on Friday July 26, 2024.

The unpaired mean difference between EPA_5μM_1 and Ctr_1 is 0.036 [95%CI 0.011, 0.063].
The p-value of the two-sided permutation t-test is 0.0266, calculated for legacy purposes only.

The unpaired mean difference between EPA_5μM_2 and Ctr_2 is 0.068 [95%CI 0.032, 0.109].
The p-value of the two-sided permutation t-test is 0.0055, calculated for legacy purposes only.

The unpaired mean difference between EPA_5μM_3 and Ctr_3 is 0.012 [95%CI -0.018, 0.043].
The p-value of the two-sided permutation t-test is 0.4823, calculated for legacy purposes only.

The unpaired mean difference between EPA_5μM_4 and Ctr_4 is -0.026 [95%CI -0.048, 0.002].
The p-value of the two-sided permutation t-test is 0.0849, calculated for legacy purposes only.

The unpaired mean difference between EPA_5μM_5 and Ctr_5 is -0.011 [95%CI -0.031, 0.005].
The p-value of the two-sided permutation t-test is 0.2624, calculated for legacy purposes only.

The unpaired mean difference between EPA_5μM_6 and Ctr_6 is 0.091 [95%CI 0.065, 0.125].
The p-value of the two-sided permutation t-test is 0.0001, calculated for legacy purposes only.

5000 bootstrap samples were taken; the confidence interval is bias-corrected and accelerated.
Any p-value reported is the probability of observing the effect size (or greater),
assuming the null hypothesis of zero difference is true.
For each p-value, 5000 reshuffles of the control and test labels were performed.
kable(unpaired5.mean_diff$boot_result |> select(-bootstraps))
control_group test_group nboots bca_ci_low bca_ci_high pct_ci_low pct_ci_high ci difference weight
Ctr_1 EPA_5μM_1 5000 0.0105000 0.0626250 0.0105000 0.0625000 95 0.036000 1278.3053
Ctr_2 EPA_5μM_2 5000 0.0320000 0.1085000 0.0315031 0.1076250 95 0.068500 575.6816
Ctr_3 EPA_5μM_3 5000 -0.0180310 0.0429689 -0.0182469 0.0428750 95 0.011875 925.5663
Ctr_4 EPA_5μM_4 5000 -0.0483460 0.0023750 -0.0494969 0.0003719 95 -0.025750 1362.6962
Ctr_5 EPA_5μM_5 5000 -0.0310000 0.0051207 -0.0300000 0.0057500 95 -0.011500 2693.9914
Ctr_6 EPA_5μM_6 5000 0.0650000 0.1250000 0.0625000 0.1225000 95 0.091250 949.9576
Minimeta Overall Test Minimeta Overall Test 5000 0.0024303 0.0274285 0.0148743 0.0152279 95 0.015034 1.0000 
dabest_plot(unpaired5.mean_diff)

Version Author Date
7a9f863 Evgenii O. Tretiakov 2024-07-26
25c1972 Evgenii O. Tretiakov 2024-07-25
5947ab6 EugOT 2024-03-20
d69bcf7 EugOT 2024-03-20

10 μM of EPA

unpaired10 <- load(df,
  x = Group, y = Measurement,
  idx = list(
    c("Ctr_1", "EPA_10μM_1"),
    c("Ctr_2", "EPA_10μM_2"),
    c("Ctr_3", "EPA_10μM_3"),
    c("Ctr_4", "EPA_10μM_4"),
    c("Ctr_5", "EPA_10μM_5"),
    c("Ctr_6", "EPA_10μM_6")
  ),
  minimeta = TRUE
)
print(unpaired10)
DABESTR v2023.9.12
==================

Good morning!
The current time is 09:51 AM on Friday July 26, 2024.

Effect size(s) with 95% confidence intervals will be computed for:
1. EPA_10μM_1 minus Ctr_1
2. EPA_10μM_2 minus Ctr_2
3. EPA_10μM_3 minus Ctr_3
4. EPA_10μM_4 minus Ctr_4
5. EPA_10μM_5 minus Ctr_5
6. EPA_10μM_6 minus Ctr_6
7. weighted delta (only for mean difference)

5000 resamples will be used to generate the effect size bootstraps.
unpaired10.mean_diff <- mean_diff(unpaired10)

print(unpaired10.mean_diff)
DABESTR v2023.9.12
==================

Good morning!
The current time is 09:51 AM on Friday July 26, 2024.

The unpaired mean difference between EPA_10μM_1 and Ctr_1 is 0.06 [95%CI 0.033, 0.093].
The p-value of the two-sided permutation t-test is 0.0026, calculated for legacy purposes only.

The unpaired mean difference between EPA_10μM_2 and Ctr_2 is 0.063 [95%CI 0.03, 0.096].
The p-value of the two-sided permutation t-test is 0.0036, calculated for legacy purposes only.

The unpaired mean difference between EPA_10μM_3 and Ctr_3 is 0.035 [95%CI 0.009, 0.064].
The p-value of the two-sided permutation t-test is 0.0376, calculated for legacy purposes only.

The unpaired mean difference between EPA_10μM_4 and Ctr_4 is 0.002 [95%CI -0.024, 0.032].
The p-value of the two-sided permutation t-test is 0.9092, calculated for legacy purposes only.

The unpaired mean difference between EPA_10μM_5 and Ctr_5 is 0.004 [95%CI -0.015, 0.021].
The p-value of the two-sided permutation t-test is 0.6694, calculated for legacy purposes only.

The unpaired mean difference between EPA_10μM_6 and Ctr_6 is 0.045 [95%CI 0.024, 0.065].
The p-value of the two-sided permutation t-test is 0.0018, calculated for legacy purposes only.

5000 bootstrap samples were taken; the confidence interval is bias-corrected and accelerated.
Any p-value reported is the probability of observing the effect size (or greater),
assuming the null hypothesis of zero difference is true.
For each p-value, 5000 reshuffles of the control and test labels were performed.
kable(unpaired10.mean_diff$boot_result |> select(-bootstraps))
control_group test_group nboots bca_ci_low bca_ci_high pct_ci_low pct_ci_high ci difference weight
Ctr_1 EPA_10μM_1 5000 0.0325000 0.0925793 0.0316250 0.0911250 95 0.0603750 923.3686
Ctr_2 EPA_10μM_2 5000 0.0305000 0.0963750 0.0300031 0.0960000 95 0.0630000 784.2698
Ctr_3 EPA_10μM_3 5000 0.0092500 0.0643750 0.0083750 0.0631250 95 0.0351250 1110.9899
Ctr_4 EPA_10μM_4 5000 -0.0242500 0.0317707 -0.0257500 0.0306250 95 0.0017500 1104.7326
Ctr_5 EPA_10μM_5 5000 -0.0153750 0.0211250 -0.0143750 0.0220000 95 0.0043750 2523.4887
Ctr_6 EPA_10μM_6 5000 0.0237500 0.0650000 0.0237500 0.0650000 95 0.0450000 1872.9097
Minimeta Overall Test Minimeta Overall Test 5000 0.0172908 0.0412704 0.0289180 0.0292622 95 0.0290195 1.0000 
dabest_plot(unpaired10.mean_diff)

Version Author Date
7a9f863 Evgenii O. Tretiakov 2024-07-26
25c1972 Evgenii O. Tretiakov 2024-07-25
5947ab6 EugOT 2024-03-20
d69bcf7 EugOT 2024-03-20

30 μM of EPA

unpaired30 <- load(df,
  x = Group, y = Measurement,
  idx = list(
    c("Ctr_1", "EPA_30μM_1"),
    c("Ctr_2", "EPA_30μM_2"),
    c("Ctr_3", "EPA_30μM_3"),
    c("Ctr_4", "EPA_30μM_4"),
    c("Ctr_5", "EPA_30μM_5"),
    c("Ctr_6", "EPA_30μM_6")
  ),
  minimeta = TRUE
)
print(unpaired30)
DABESTR v2023.9.12
==================

Good morning!
The current time is 09:51 AM on Friday July 26, 2024.

Effect size(s) with 95% confidence intervals will be computed for:
1. EPA_30μM_1 minus Ctr_1
2. EPA_30μM_2 minus Ctr_2
3. EPA_30μM_3 minus Ctr_3
4. EPA_30μM_4 minus Ctr_4
5. EPA_30μM_5 minus Ctr_5
6. EPA_30μM_6 minus Ctr_6
7. weighted delta (only for mean difference)

5000 resamples will be used to generate the effect size bootstraps.
unpaired30.mean_diff <- mean_diff(unpaired30)

print(unpaired30.mean_diff)
DABESTR v2023.9.12
==================

Good morning!
The current time is 09:51 AM on Friday July 26, 2024.

The unpaired mean difference between EPA_30μM_1 and Ctr_1 is 0.096 [95%CI 0.007, 0.14].
The p-value of the two-sided permutation t-test is 0.0175, calculated for legacy purposes only.

The unpaired mean difference between EPA_30μM_2 and Ctr_2 is 0.1 [95%CI 0.061, 0.136].
The p-value of the two-sided permutation t-test is 0.0002, calculated for legacy purposes only.

The unpaired mean difference between EPA_30μM_3 and Ctr_3 is 0.091 [95%CI 0.059, 0.123].
The p-value of the two-sided permutation t-test is 0.0001, calculated for legacy purposes only.

The unpaired mean difference between EPA_30μM_4 and Ctr_4 is 0.087 [95%CI 0.057, 0.117].
The p-value of the two-sided permutation t-test is 0.0001, calculated for legacy purposes only.

The unpaired mean difference between EPA_30μM_5 and Ctr_5 is 0.069 [95%CI 0.043, 0.116].
The p-value of the two-sided permutation t-test is 0.0031, calculated for legacy purposes only.

The unpaired mean difference between EPA_30μM_6 and Ctr_6 is 0.129 [95%CI 0.108, 0.145].
The p-value of the two-sided permutation t-test is 0.0000, calculated for legacy purposes only.

5000 bootstrap samples were taken; the confidence interval is bias-corrected and accelerated.
Any p-value reported is the probability of observing the effect size (or greater),
assuming the null hypothesis of zero difference is true.
For each p-value, 5000 reshuffles of the control and test labels were performed.
kable(unpaired30.mean_diff$boot_result |> select(-bootstraps))
control_group test_group nboots bca_ci_low bca_ci_high pct_ci_low pct_ci_high ci difference weight
Ctr_1 EPA_30μM_1 5000 0.0070740 0.1397500 0.0288781 0.1503750 95 0.0962500 225.2778
Ctr_2 EPA_30μM_2 5000 0.0610000 0.1357500 0.0618813 0.1367500 95 0.0996250 619.8153
Ctr_3 EPA_30μM_3 5000 0.0587500 0.1227395 0.0585031 0.1224969 95 0.0905000 850.7148
Ctr_4 EPA_30μM_4 5000 0.0573750 0.1167127 0.0570000 0.1165000 95 0.0866250 971.4211
Ctr_5 EPA_30μM_5 5000 0.0426250 0.1157298 0.0385000 0.1073750 95 0.0693750 738.6352
Ctr_6 EPA_30μM_6 5000 0.1075000 0.1450000 0.1087500 0.1462500 95 0.1287500 2338.2046
Minimeta Overall Test Minimeta Overall Test 5000 0.0921689 0.1152220 0.1037444 0.1040722 95 0.1039085 1.0000 
dabest_plot(unpaired30.mean_diff)

Version Author Date
7a9f863 Evgenii O. Tretiakov 2024-07-26
25c1972 Evgenii O. Tretiakov 2024-07-25
5947ab6 EugOT 2024-03-20
d69bcf7 EugOT 2024-03-20 

sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.4 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;  LAPACK version 3.10.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

time zone: Etc/UTC
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] skimr_2.1.5          magrittr_2.0.3       lubridate_1.9.3     
 [4] forcats_1.0.0        stringr_1.5.1        dplyr_1.1.4         
 [7] purrr_1.0.2          readr_2.1.5          tidyr_1.3.1         
[10] tibble_3.2.1         ggplot2_3.5.1        tidyverse_2.0.0.9000
[13] dabestr_2023.9.12    RColorBrewer_1.1-3   knitr_1.47          
[16] here_1.0.1           workflowr_1.7.1     

loaded via a namespace (and not attached):
 [1] beeswarm_0.4.0    gtable_0.3.5      xfun_0.45         bslib_0.7.0      
 [5] processx_3.8.4    callr_3.7.6       tzdb_0.4.0        vctrs_0.6.5      
 [9] tools_4.4.0       ps_1.7.6          generics_0.1.3    parallel_4.4.0   
[13] fansi_1.0.6       highr_0.11        pkgconfig_2.0.3   lifecycle_1.0.4  
[17] farver_2.1.2      compiler_4.4.0    git2r_0.33.0      munsell_0.5.1    
[21] ggsci_3.2.0       repr_1.1.7        getPass_0.2-4     vipor_0.4.7      
[25] httpuv_1.6.15     htmltools_0.5.8.1 sass_0.4.9        yaml_2.3.8       
[29] crayon_1.5.2      later_1.3.2       pillar_1.9.0      jquerylib_0.1.4  
[33] whisker_0.4.1     ggmin_0.0.0.9000  cachem_1.1.0      boot_1.3-30      
[37] tidyselect_1.2.1  digest_0.6.35     stringi_1.8.4     labeling_0.4.3   
[41] cowplot_1.1.3     rprojroot_2.0.4   fastmap_1.2.0     grid_4.4.0       
[45] colorspace_2.1-0  cli_3.6.2         base64enc_0.1-3   utf8_1.2.4       
[49] effsize_0.8.1     withr_3.0.0       scales_1.3.0      promises_1.3.0   
[53] bit64_4.0.5       ggbeeswarm_0.7.2  timechange_0.3.0  rmarkdown_2.27   
[57] httr_1.4.7        bit_4.0.5         hms_1.1.3         evaluate_0.24.0  
[61] rlang_1.1.4       Rcpp_1.0.12       glue_1.7.0        rstudioapi_0.16.0
[65] vroom_1.6.5       jsonlite_1.8.8    R6_2.5.1          fs_1.6.4