This function replicates counts from a real-world dataset.
Usage
sccomp_replicate(
fit,
formula_composition = NULL,
formula_variability = NULL,
number_of_draws = 1,
mcmc_seed = sample_seed(),
cache_stan_model = sccomp_stan_models_cache_dir
)Arguments
- fit
The result of sccomp_estimate.
- formula_composition
A formula. The formula describing the model for differential abundance, for example ~treatment. This formula can be a sub-formula of your estimated model; in this case all other factor will be factored out.
- formula_variability
A formula. The formula describing the model for differential variability, for example ~treatment. In most cases, if differentially variability is of interest, the formula should only include the factor of interest as a large anount of data is needed to define variability depending to each factors. This formula can be a sub-formula of your estimated model; in this case all other factor will be factored out.
- number_of_draws
An integer. How may copies of the data you want to draw from the model joint posterior distribution.
- mcmc_seed
An integer. Used for Markov-chain Monte Carlo reproducibility. By default a random number is sampled from 1 to 999999. This itself can be controlled by set.seed()
- cache_stan_model
A character string specifying the cache directory for compiled Stan models. The sccomp version will be automatically appended to ensure version isolation. Default is
sccomp_stan_models_cache_dirwhich points to~/.sccomp_models.
Value
A tibble tbl with cell_group-wise statistics
A tibble (tbl), with the following columns:
cell_group - A character column representing the cell group being tested.
sample - A factor column representing the sample name from which data was generated.
generated_proportions - A numeric column representing the proportions generated from the model.
generated_counts - An integer column representing the counts generated from the model.
replicate - An integer column representing the replicate number, where each row corresponds to a different replicate of the data.
References
S. Mangiola, A.J. Roth-Schulze, M. Trussart, E. Zozaya-Valdés, M. Ma, Z. Gao, A.F. Rubin, T.P. Speed, H. Shim, & A.T. Papenfuss, sccomp: Robust differential composition and variability analysis for single-cell data, Proc. Natl. Acad. Sci. U.S.A. 120 (33) e2203828120, https://doi.org/10.1073/pnas.2203828120 (2023).
Examples
print("cmdstanr is needed to run this example.")
#> [1] "cmdstanr is needed to run this example."
# Note: Before running the example, ensure that the 'cmdstanr' package is installed:
# install.packages("cmdstanr", repos = c("https://stan-dev.r-universe.dev/", getOption("repos")))
# \donttest{
if (instantiate::stan_cmdstan_exists() && .Platform$OS.type == "unix") {
data("counts_obj")
sccomp_estimate(
counts_obj,
~ type, ~1, "sample", "cell_group", "count",
cores = 1
) |>
sccomp_replicate()
}
#> sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
#> sccomp says: estimation
#> sccomp says: the composition design matrix has columns: (Intercept), typecancer
#> sccomp says: the variability design matrix has columns: (Intercept)
#> Loading model from cache...
#> Path [1] :Initial log joint density = -481857.352512
#> Path [1] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 55 -4.788e+05 1.072e-02 2.772e-01 5.264e-01 1.000e+00 3071 -3.708e+03 -3.708e+03
#> Path [1] :Best Iter: [55] ELBO (-3707.571304) evaluations: (3071)
#> Path [2] :Initial log joint density = -481263.536047
#> Path [2] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 52 -4.788e+05 5.827e-03 2.019e-01 9.344e-01 9.344e-01 2832 -3.706e+03 -3.721e+03
#> Path [2] :Best Iter: [51] ELBO (-3706.222412) evaluations: (2832)
#> Path [3] :Initial log joint density = -481682.009281
#> Path [3] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 54 -4.788e+05 1.229e-02 2.397e-01 1.000e+00 1.000e+00 2995 -3.706e+03 -3.709e+03
#> Path [3] :Best Iter: [53] ELBO (-3705.821053) evaluations: (2995)
#> Path [4] :Initial log joint density = -482140.254034
#> Path [4] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 62 -4.788e+05 7.059e-03 2.271e-01 1.000e+00 1.000e+00 3674 -3.699e+03 -3.703e+03
#> Path [4] :Best Iter: [58] ELBO (-3699.287060) evaluations: (3674)
#> Path [5] :Initial log joint density = -481199.527570
#> Path [5] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 56 -4.788e+05 8.464e-03 2.567e-01 1.000e+00 1.000e+00 3262 -3.706e+03 -3.701e+03
#> Path [5] :Best Iter: [56] ELBO (-3701.142608) evaluations: (3262)
#> Path [6] :Initial log joint density = -481725.049984
#> Path [6] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 60 -4.788e+05 1.072e-02 2.604e-01 1.000e+00 1.000e+00 3535 -3.704e+03 -3.702e+03
#> Path [6] :Best Iter: [60] ELBO (-3702.251819) evaluations: (3535)
#> Path [7] :Initial log joint density = -482410.654722
#> Path [7] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 55 -4.788e+05 1.476e-02 2.443e-01 1.000e+00 1.000e+00 3028 -3.708e+03 -3.702e+03
#> Path [7] :Best Iter: [55] ELBO (-3701.535344) evaluations: (3028)
#> Path [8] :Initial log joint density = -481492.383749
#> Path [8] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 51 -4.788e+05 5.169e-03 1.952e-01 8.410e-01 8.410e-01 2797 -3.705e+03 -3.730e+03
#> Path [8] :Best Iter: [49] ELBO (-3705.492961) evaluations: (2797)
#> Path [9] :Initial log joint density = -481764.651131
#> Path [9] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 56 -4.788e+05 5.950e-03 2.214e-01 8.903e-01 8.903e-01 3195 -3.708e+03 -3.709e+03
#> Path [9] :Best Iter: [55] ELBO (-3707.559354) evaluations: (3195)
#> Path [10] :Initial log joint density = -481473.116263
#> Path [10] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 55 -4.788e+05 6.949e-03 2.365e-01 9.878e-01 9.878e-01 3106 -3.708e+03 -3.708e+03
#> Path [10] :Best Iter: [55] ELBO (-3708.196652) evaluations: (3106)
#> Path [11] :Initial log joint density = -481891.986901
#> Path [11] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 58 -4.788e+05 4.274e-03 3.115e-01 6.483e-01 6.483e-01 3434 -3.700e+03 -3.712e+03
#> Path [11] :Best Iter: [55] ELBO (-3700.273471) evaluations: (3434)
#> Path [12] :Initial log joint density = -485313.233904
#> Path [12] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 59 -4.788e+05 1.410e-02 2.247e-01 1.000e+00 1.000e+00 3533 -3.701e+03 -3.703e+03
#> Path [12] :Best Iter: [58] ELBO (-3701.117858) evaluations: (3533)
#> Path [13] :Initial log joint density = -481941.573464
#> Path [13] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 62 -4.788e+05 8.342e-03 2.283e-01 1.000e+00 1.000e+00 3620 -3.701e+03 -3.699e+03
#> Path [13] :Best Iter: [62] ELBO (-3698.763517) evaluations: (3620)
#> Path [14] :Initial log joint density = -483622.857925
#> Path [14] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 6.939e-03 2.252e-01 1.000e+00 1.000e+00 2957 -3.707e+03 -3.718e+03
#> Path [14] :Best Iter: [48] ELBO (-3706.710122) evaluations: (2957)
#> Path [15] :Initial log joint density = -481675.727968
#> Path [15] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 55 -4.788e+05 7.896e-03 3.260e-01 1.000e+00 1.000e+00 3122 -3.710e+03 -3.706e+03
#> Path [15] :Best Iter: [55] ELBO (-3706.202511) evaluations: (3122)
#> Path [16] :Initial log joint density = -482002.369050
#> Path [16] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 61 -4.788e+05 4.629e-03 1.253e-01 8.056e-01 8.056e-01 3591 -3.702e+03 -3.713e+03
#> Path [16] :Best Iter: [59] ELBO (-3702.227555) evaluations: (3591)
#> Path [17] :Initial log joint density = -481920.783513
#> Path [17] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 57 -4.788e+05 7.711e-03 2.751e-01 7.667e-01 7.667e-01 3265 -3.702e+03 -3.712e+03
#> Path [17] :Best Iter: [55] ELBO (-3702.310919) evaluations: (3265)
#> Path [18] :Initial log joint density = -482555.134240
#> Path [18] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 59 -4.788e+05 1.475e-02 2.071e-01 1.000e+00 1.000e+00 3423 -3.703e+03 -3.702e+03
#> Path [18] :Best Iter: [59] ELBO (-3702.209607) evaluations: (3423)
#> Path [19] :Initial log joint density = -483990.222971
#> Path [19] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 54 -4.788e+05 1.523e-02 2.670e-01 1.000e+00 1.000e+00 2986 -3.709e+03 -3.713e+03
#> Path [19] :Best Iter: [45] ELBO (-3708.950406) evaluations: (2986)
#> Path [20] :Initial log joint density = -482014.813191
#> Path [20] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 64 -4.788e+05 1.657e-02 3.120e-01 5.113e-01 1.000e+00 4007 -3.697e+03 -3.704e+03
#> Path [20] :Best Iter: [63] ELBO (-3697.371682) evaluations: (4007)
#> Path [21] :Initial log joint density = -481670.996419
#> Path [21] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 56 -4.788e+05 1.855e-02 2.302e-01 1.000e+00 1.000e+00 3257 -3.704e+03 -3.701e+03
#> Path [21] :Best Iter: [56] ELBO (-3701.343670) evaluations: (3257)
#> Path [22] :Initial log joint density = -481388.051225
#> Path [22] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 2.757e-03 2.124e-01 7.642e-01 7.642e-01 2961 -3.702e+03 -3.722e+03
#> Path [22] :Best Iter: [51] ELBO (-3701.973754) evaluations: (2961)
#> Path [23] :Initial log joint density = -481692.347937
#> Path [23] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 1.635e-02 4.033e-01 1.000e+00 1.000e+00 2854 -3.705e+03 -3.710e+03
#> Path [23] :Best Iter: [51] ELBO (-3704.532218) evaluations: (2854)
#> Path [24] :Initial log joint density = -485362.943854
#> Path [24] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 57 -4.788e+05 1.433e-02 3.109e-01 1.000e+00 1.000e+00 3298 -3.700e+03 -3.699e+03
#> Path [24] :Best Iter: [57] ELBO (-3699.150335) evaluations: (3298)
#> Path [25] :Initial log joint density = -482234.963368
#> Path [25] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 63 -4.788e+05 7.803e-03 2.127e-01 1.000e+00 1.000e+00 3772 -3.700e+03 -3.707e+03
#> Path [25] :Best Iter: [61] ELBO (-3699.817680) evaluations: (3772)
#> Path [26] :Initial log joint density = -481655.402253
#> Path [26] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 8.741e-03 2.851e-01 1.000e+00 1.000e+00 3008 -3.706e+03 -3.715e+03
#> Path [26] :Best Iter: [48] ELBO (-3705.940808) evaluations: (3008)
#> Path [27] :Initial log joint density = -481701.413051
#> Path [27] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 57 -4.788e+05 4.501e-03 2.471e-01 7.866e-01 7.866e-01 3160 -3.702e+03 -3.717e+03
#> Path [27] :Best Iter: [55] ELBO (-3702.091432) evaluations: (3160)
#> Path [28] :Initial log joint density = -481836.262825
#> Path [28] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 56 -4.788e+05 1.455e-02 3.698e-01 1.000e+00 1.000e+00 3229 -3.704e+03 -3.711e+03
#> Path [28] :Best Iter: [55] ELBO (-3704.314872) evaluations: (3229)
#> Path [29] :Initial log joint density = -481614.553185
#> Path [29] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 54 -4.788e+05 9.436e-03 2.493e-01 1.000e+00 1.000e+00 3036 -3.706e+03 -3.712e+03
#> Path [29] :Best Iter: [42] ELBO (-3705.607002) evaluations: (3036)
#> Path [30] :Initial log joint density = -481713.050002
#> Path [30] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 54 -4.788e+05 1.191e-02 3.243e-01 1.000e+00 1.000e+00 2991 -3.707e+03 -3.711e+03
#> Path [30] :Best Iter: [43] ELBO (-3707.342788) evaluations: (2991)
#> Path [31] :Initial log joint density = -481273.168557
#> Path [31] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 1.180e-02 3.834e-01 1.000e+00 1.000e+00 2991 -3.708e+03 -3.724e+03
#> Path [31] :Best Iter: [46] ELBO (-3708.080784) evaluations: (2991)
#> Path [32] :Initial log joint density = -482887.927356
#> Path [32] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 57 -4.788e+05 5.487e-03 2.747e-01 8.353e-01 8.353e-01 3240 -3.701e+03 -3.712e+03
#> Path [32] :Best Iter: [55] ELBO (-3701.287790) evaluations: (3240)
#> Path [33] :Initial log joint density = -481609.144559
#> Path [33] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 56 -4.788e+05 5.730e-03 1.959e-01 1.000e+00 1.000e+00 3109 -3.709e+03 -3.710e+03
#> Path [33] :Best Iter: [52] ELBO (-3708.953872) evaluations: (3109)
#> Path [34] :Initial log joint density = -481418.022135
#> Path [34] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 55 -4.788e+05 3.530e-03 3.964e-01 5.809e-01 5.809e-01 3105 -3.705e+03 -3.716e+03
#> Path [34] :Best Iter: [44] ELBO (-3705.113596) evaluations: (3105)
#> Path [35] :Initial log joint density = -482064.760528
#> Path [35] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 62 -4.788e+05 9.423e-03 2.904e-01 1.000e+00 1.000e+00 3769 -3.701e+03 -3.703e+03
#> Path [35] :Best Iter: [58] ELBO (-3700.742872) evaluations: (3769)
#> Path [36] :Initial log joint density = -481767.303765
#> Path [36] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 58 -4.788e+05 1.773e-02 2.734e-01 9.345e-01 9.345e-01 3385 -3.698e+03 -3.706e+03
#> Path [36] :Best Iter: [56] ELBO (-3697.731451) evaluations: (3385)
#> Path [37] :Initial log joint density = -481623.902326
#> Path [37] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 56 -4.788e+05 5.502e-03 2.003e-01 1.000e+00 1.000e+00 3175 -3.705e+03 -3.705e+03
#> Path [37] :Best Iter: [56] ELBO (-3704.765860) evaluations: (3175)
#> Path [38] :Initial log joint density = -481752.940232
#> Path [38] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 8.280e-03 3.445e-01 4.339e-01 1.000e+00 2995 -3.708e+03 -3.724e+03
#> Path [38] :Best Iter: [43] ELBO (-3707.820251) evaluations: (2995)
#> Path [39] :Initial log joint density = -484948.503389
#> Path [39] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 58 -4.788e+05 1.485e-02 2.450e-01 1.000e+00 1.000e+00 3421 -3.699e+03 -3.700e+03
#> Path [39] :Best Iter: [56] ELBO (-3698.527984) evaluations: (3421)
#> Path [40] :Initial log joint density = -481848.889677
#> Path [40] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 52 -4.788e+05 1.201e-02 2.555e-01 1.000e+00 1.000e+00 2833 -3.707e+03 -3.715e+03
#> Path [40] :Best Iter: [50] ELBO (-3707.268683) evaluations: (2833)
#> Path [41] :Initial log joint density = -481662.350201
#> Path [41] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 9.771e-03 2.258e-01 8.547e-01 8.547e-01 3057 -3.706e+03 -3.729e+03
#> Path [41] :Best Iter: [46] ELBO (-3705.677210) evaluations: (3057)
#> Path [42] :Initial log joint density = -481495.192395
#> Path [42] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 57 -4.788e+05 5.654e-03 2.112e-01 1.000e+00 1.000e+00 3136 -3.706e+03 -3.704e+03
#> Path [42] :Best Iter: [57] ELBO (-3703.954043) evaluations: (3136)
#> Path [43] :Initial log joint density = -481617.743788
#> Path [43] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 59 -4.788e+05 1.126e-02 2.771e-01 1.000e+00 1.000e+00 3345 -3.702e+03 -3.703e+03
#> Path [43] :Best Iter: [55] ELBO (-3701.908004) evaluations: (3345)
#> Path [44] :Initial log joint density = -481347.701139
#> Path [44] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 52 -4.788e+05 1.230e-02 3.035e-01 1.000e+00 1.000e+00 2874 -3.707e+03 -3.711e+03
#> Path [44] :Best Iter: [41] ELBO (-3706.825189) evaluations: (2874)
#> Path [45] :Initial log joint density = -481616.840901
#> Path [45] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 54 -4.788e+05 7.657e-03 2.598e-01 1.000e+00 1.000e+00 3093 -3.708e+03 -3.711e+03
#> Path [45] :Best Iter: [52] ELBO (-3707.982397) evaluations: (3093)
#> Path [46] :Initial log joint density = -481830.077846
#> Path [46] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 56 -4.788e+05 5.780e-03 1.912e-01 1.000e+00 1.000e+00 3158 -3.708e+03 -3.708e+03
#> Path [46] :Best Iter: [56] ELBO (-3707.677671) evaluations: (3158)
#> Path [47] :Initial log joint density = -481725.120970
#> Path [47] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 53 -4.788e+05 5.041e-03 1.511e-01 1.000e+00 1.000e+00 2925 -3.707e+03 -3.716e+03
#> Path [47] :Best Iter: [50] ELBO (-3706.618925) evaluations: (2925)
#> Path [48] :Initial log joint density = -481673.716321
#> Path [48] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 58 -4.788e+05 1.061e-02 2.269e-01 1.000e+00 1.000e+00 3343 -3.700e+03 -3.699e+03
#> Path [48] :Best Iter: [58] ELBO (-3698.712217) evaluations: (3343)
#> Path [49] :Initial log joint density = -481548.724803
#> Path [49] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 55 -4.788e+05 5.468e-03 3.233e-01 6.704e-01 6.704e-01 3121 -3.712e+03 -3.717e+03
#> Path [49] :Best Iter: [40] ELBO (-3712.300190) evaluations: (3121)
#> Path [50] :Initial log joint density = -482713.963241
#> Path [50] : Iter log prob ||dx|| ||grad|| alpha alpha0 # evals ELBO Best ELBO Notes
#> 58 -4.788e+05 1.371e-02 2.222e-01 1.000e+00 1.000e+00 3437 -3.700e+03 -3.698e+03
#> Path [50] :Best Iter: [58] ELBO (-3697.583389) evaluations: (3437)
#> Finished in 13.5 seconds.
#> sccomp says: to do hypothesis testing run `sccomp_test()`,
#> the `test_composition_above_logit_fold_change` = 0.1 equates to a change of ~10%, and
#> 0.7 equates to ~100% increase, if the baseline is ~0.1 proportion.
#> Use `sccomp_proportional_fold_change` to convert c_effect (linear) to proportion difference (non-linear).
#> sccomp says: auto-cleanup removed 1 draw files from 'sccomp_draws_files'
#> Loading model from cache...
#> Running standalone generated quantities after 1 MCMC chain, with 1 thread(s) per chain...
#>
#> Chain 1 finished in 0.0 seconds.
#> # A tibble: 720 × 5
#> cell_group sample generated_proportions generated_counts replicate
#> <chr> <fct> <dbl> <int> <int>
#> 1 B1 10x_6K 0.0387 193 1
#> 2 B1 10x_8K 0.0222 110 1
#> 3 B1 GSE115189 0.0721 360 1
#> 4 B1 SCP345_580 0.0738 368 1
#> 5 B1 SCP345_860 0.0384 191 1
#> 6 B1 SCP424_pbmc1 0.0525 262 1
#> 7 B1 SCP424_pbmc2 0.0701 350 1
#> 8 B1 SCP591 0.0676 337 1
#> 9 B1 SI-GA-E5 0.0422 210 1
#> 10 B1 SI-GA-E7 0.0185 92 1
#> # ℹ 710 more rows
# }