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} </style> <div class="fluid-row" id="header"> <h1 class="title toc-ignore">Marginal Distribution of <span class="math inline">\(z\)</span> Scores: Null</h1> <h4 class="author"><em>Lei Sun</em></h4> <h4 class="date"><em>2017-04-25</em></h4> </div> <p><strong>Last updated:</strong> 2018-05-15</p> <strong>workflowr checks:</strong> <small>(Click a bullet for more information)</small> <ul> <li> <details> <p><summary> <strong style="color:blue;">✔</strong> <strong>R Markdown file:</strong> up-to-date </summary></p> <p>Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.</p> </details> </li> <li> <details> <p><summary> <strong style="color:blue;">✔</strong> <strong>Environment:</strong> empty </summary></p> <p>Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.</p> </details> </li> <li> <details> <p><summary> <strong style="color:blue;">✔</strong> <strong>Seed:</strong> <code>set.seed(12345)</code> </summary></p> <p>The command <code>set.seed(12345)</code> was run prior to running the code in the R Markdown file. 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The version displayed above was the version of the Git repository at the time these results were generated. <br><br> Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use <code>wflow_publish</code> or <code>wflow_git_commit</code>). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated: <pre><code> Ignored files: Ignored: .DS_Store Ignored: .Rhistory Ignored: .Rproj.user/ Ignored: analysis/.DS_Store Ignored: analysis/BH_robustness_cache/ Ignored: analysis/FDR_Null_cache/ Ignored: analysis/FDR_null_betahat_cache/ Ignored: analysis/Rmosek_cache/ Ignored: analysis/StepDown_cache/ Ignored: analysis/alternative2_cache/ Ignored: analysis/alternative_cache/ Ignored: analysis/ash_gd_cache/ Ignored: analysis/average_cor_gtex_2_cache/ Ignored: analysis/average_cor_gtex_cache/ Ignored: analysis/brca_cache/ Ignored: analysis/cash_deconv_cache/ Ignored: analysis/cash_fdr_1_cache/ Ignored: analysis/cash_fdr_2_cache/ Ignored: analysis/cash_fdr_3_cache/ Ignored: analysis/cash_fdr_4_cache/ Ignored: analysis/cash_fdr_5_cache/ Ignored: analysis/cash_fdr_6_cache/ Ignored: analysis/cash_plots_cache/ Ignored: analysis/cash_sim_1_cache/ Ignored: analysis/cash_sim_2_cache/ Ignored: analysis/cash_sim_3_cache/ Ignored: analysis/cash_sim_4_cache/ Ignored: analysis/cash_sim_5_cache/ Ignored: analysis/cash_sim_6_cache/ Ignored: analysis/cash_sim_7_cache/ Ignored: analysis/correlated_z_2_cache/ Ignored: analysis/correlated_z_3_cache/ Ignored: analysis/correlated_z_cache/ Ignored: analysis/create_null_cache/ Ignored: analysis/cutoff_null_cache/ Ignored: analysis/design_matrix_2_cache/ Ignored: analysis/design_matrix_cache/ Ignored: analysis/diagnostic_ash_cache/ Ignored: analysis/diagnostic_correlated_z_2_cache/ Ignored: analysis/diagnostic_correlated_z_3_cache/ Ignored: analysis/diagnostic_correlated_z_cache/ Ignored: analysis/diagnostic_plot_2_cache/ Ignored: analysis/diagnostic_plot_cache/ Ignored: analysis/efron_leukemia_cache/ Ignored: analysis/fitting_normal_cache/ Ignored: analysis/gaussian_derivatives_2_cache/ Ignored: analysis/gaussian_derivatives_3_cache/ Ignored: analysis/gaussian_derivatives_4_cache/ Ignored: analysis/gaussian_derivatives_5_cache/ Ignored: analysis/gaussian_derivatives_cache/ Ignored: analysis/gd-ash_cache/ Ignored: analysis/gd_delta_cache/ Ignored: analysis/gd_lik_2_cache/ Ignored: analysis/gd_lik_cache/ Ignored: analysis/gd_w_cache/ Ignored: analysis/knockoff_10_cache/ Ignored: analysis/knockoff_2_cache/ Ignored: analysis/knockoff_3_cache/ Ignored: analysis/knockoff_4_cache/ Ignored: analysis/knockoff_5_cache/ Ignored: analysis/knockoff_6_cache/ Ignored: analysis/knockoff_7_cache/ Ignored: analysis/knockoff_8_cache/ Ignored: analysis/knockoff_9_cache/ Ignored: analysis/knockoff_cache/ Ignored: analysis/knockoff_var_cache/ Ignored: analysis/marginal_z_alternative_cache/ Ignored: analysis/marginal_z_cache/ Ignored: analysis/mosek_reg_2_cache/ Ignored: analysis/mosek_reg_4_cache/ Ignored: analysis/mosek_reg_5_cache/ Ignored: analysis/mosek_reg_6_cache/ Ignored: analysis/mosek_reg_cache/ Ignored: analysis/pihat0_null_cache/ Ignored: analysis/plot_diagnostic_cache/ Ignored: analysis/poster_obayes17_cache/ Ignored: analysis/real_data_simulation_2_cache/ Ignored: analysis/real_data_simulation_3_cache/ Ignored: analysis/real_data_simulation_4_cache/ Ignored: analysis/real_data_simulation_5_cache/ Ignored: analysis/real_data_simulation_cache/ Ignored: analysis/rmosek_primal_dual_2_cache/ Ignored: analysis/rmosek_primal_dual_cache/ Ignored: analysis/seqgendiff_cache/ Ignored: analysis/simulated_correlated_null_2_cache/ Ignored: analysis/simulated_correlated_null_3_cache/ Ignored: analysis/simulated_correlated_null_cache/ Ignored: analysis/simulation_real_se_2_cache/ Ignored: analysis/simulation_real_se_cache/ Ignored: analysis/smemo_2_cache/ Ignored: data/LSI/ Ignored: docs/.DS_Store Ignored: docs/figure/.DS_Store Ignored: output/fig/ </code></pre> Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes. </details> </li> </ul> <details> <summary> <small><strong>Expand here to see past versions:</strong></small> </summary> <ul> <table style="border-collapse:separate; border-spacing:5px;"> <thead> <tr> <th style="text-align:left;"> File </th> <th style="text-align:left;"> Version </th> <th style="text-align:left;"> Author </th> <th style="text-align:left;"> Date </th> <th style="text-align:left;"> Message </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/LSun/truncash/e05bc836b3c74dc6ebca415afb5938675d6c5436/docs/marginal_z.html" target="_blank">e05bc83</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2018-05-12 </td> <td style="text-align:left;"> Update to 1.0 </td> </tr> <tr> <td style="text-align:left;"> rmd </td> <td style="text-align:left;"> <a href="https://github.com/LSun/truncash/blob/cc0ab8379469bc3726f1508cd81e4ecd6fef1b1a/analysis/marginal_z.rmd" target="_blank">cc0ab83</a> </td> <td style="text-align:left;"> Lei Sun </td> <td style="text-align:left;"> 2018-05-11 </td> <td style="text-align:left;"> update </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/LSun/truncash/0f36d998db26444c5dd01502ea1af7fbd1129b22/docs/marginal_z.html" target="_blank">0f36d99</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2017-12-21 </td> <td style="text-align:left;"> Build site. </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/LSun/truncash/853a484bfacf347e109f6c8fb3ffaab5f4d6cc02/docs/marginal_z.html" target="_blank">853a484</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2017-11-07 </td> <td style="text-align:left;"> Build site. </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/LSun/truncash/1ea081a9eeb7fd3101271eeefe10ef8be9993622/docs/marginal_z.html" target="_blank">1ea081a</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2017-07-03 </td> <td style="text-align:left;"> sites </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/LSun/truncash/b6bed279e2c87ed14606ec7a73dad73414ef51a0/docs/marginal_z.html" target="_blank">b6bed27</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2017-05-09 </td> <td style="text-align:left;"> marginal null </td> </tr> <tr> <td style="text-align:left;"> rmd </td> <td style="text-align:left;"> <a href="https://github.com/LSun/truncash/blob/62645294254672b1570f1f47749e5c42ec70175e/analysis/marginal_z.rmd" target="_blank">6264529</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2017-05-09 </td> <td style="text-align:left;"> marginal null </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/LSun/truncash/e5c73aef91afd535abfe8369767f24f1f03ef953/docs/marginal_z.html" target="_blank">e5c73ae</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2017-05-05 </td> <td style="text-align:left;"> marginal </td> </tr> <tr> <td style="text-align:left;"> rmd </td> <td style="text-align:left;"> <a href="https://github.com/LSun/truncash/blob/8206370b6c1bbc96998c1c719ab59b61c38570fe/analysis/marginal_z.rmd" target="_blank">8206370</a> </td> <td style="text-align:left;"> LSun </td> <td style="text-align:left;"> 2017-05-05 </td> <td style="text-align:left;"> marginal </td> </tr> </tbody> </table> </ul> </details> <hr /> <p><strong>This simulation can be seen as an enhanced version of <a href="ExtremeOccurrence.html">a previous simulation</a>.</strong></p> <div id="introduction" class="section level2"> <h2>Introduction</h2> <p>An assumption of using <a href="gaussian_derivatives.html">Gaussian derivatives</a> to fit correlated null <span class="math inline">\(z\)</span> scores is that each of these <span class="math inline">\(z\)</span> scores should actually be null. That is, for <span class="math inline">\(n\)</span> <span class="math inline">\(z\)</span> scores <span class="math inline">\(z_1, \ldots, z_n\)</span>, although the correlation between <span class="math inline">\(z_i\)</span> and <span class="math inline">\(z_j\)</span> are not necessarily zero, the marginal distribution of <span class="math inline">\(z_i\)</span>, <span class="math inline">\(\forall i\)</span>, should be <span class="math inline">\(N\left(0, 1\right)\)</span>.</p> <p>However, in practice, it’s not easy to check whether these correlated <span class="math inline">\(z\)</span> scores are truly marginally <span class="math inline">\(N\left(0, 1\right)\)</span>. <a href="correlated_z.html">We’ve seen</a> that their historgram could be far from normal. Further more, <span class="math inline">\(z\)</span> scores in different data sets are distorted by different correlation structures. Therefore, we don’t have replicates here; that is, each data set is one single realization of a lot of random variables under correlation.</p> <p>For our data sets in particular, let <span class="math inline">\(Z = \left[z_{ij}\right]_{m \times n}\)</span> be the matrix of <span class="math inline">\(z\)</span> scores. Each <span class="math inline">\(z_{ij}\)</span> denotes the gene differential expression <span class="math inline">\(z\)</span> score for gene <span class="math inline">\(j\)</span> in the data set <span class="math inline">\(i\)</span>. Since all of these <span class="math inline">\(z\)</span> scores are obtained from the same tissue, theoretically they should all be marginally <span class="math inline">\(N\left(0, 1\right)\)</span>.</p> <p>Each row is a data set, consisting of <span class="math inline">\(10K\)</span> realized <span class="math inline">\(z\)</span> scores presumably marginally <span class="math inline">\(N\left(0, 1\right)\)</span>, whose empirical distribution distorted by correlation. If we plot the histogram of each row, it is grossly not <span class="math inline">\(N\left(0, 1\right)\)</span> due to correlation. Therefore, it’s not easy to verify that they are truly marginally <span class="math inline">\(N\left(0, 1\right)\)</span>.</p> <p>Here are two pieces of evidence that they are. Let’s take a look one by one, compared with the independent <span class="math inline">\(z\)</span> scores case.</p> <pre class="r"><code>z.null <- read.table("../output/z_null_liver_777.txt") n = ncol(z.null) m = nrow(z.null)</code></pre> <pre class="r"><code>set.seed(777) z.sim = matrix(rnorm(m * n), nrow = m, ncol = n)</code></pre> </div> <div id="row-wise-eleftf_nleftzrightright-phileftzright" class="section level2"> <h2>Row-wise: <span class="math inline">\(E\left[F_n\left(z\right)\right] = \Phi\left(z\right)\)</span></h2> <p>Let <span class="math inline">\(F_n^{R_i}\left(z\right)\)</span> be the empirical CDF of <span class="math inline">\(p\)</span> correlated <span class="math inline">\(z\)</span> scores in row <span class="math inline">\(i\)</span>. For any <span class="math inline">\(i\)</span>, <span class="math inline">\(F_n^{R_i}\left(z\right)\)</span> should be conspicuously different from <span class="math inline">\(\Phi\left(z\right)\)</span>, yet on average, <span class="math inline">\(E\left[F_n^{R_i}\left(z\right)\right]\)</span> should be equal to <span class="math inline">\(\Phi\left(z\right)\)</span>, if all <span class="math inline">\(z\)</span> scores are marginally <span class="math inline">\(N\left(0, 1\right)\)</span>.</p> <p>In order to check that, we can borrow <a href="index.html">Prof. Michael Stein’s insight</a> to look at the tail events, or empirical CDF.</p> <p>For each row, let <span class="math inline">\(\alpha\)</span> be a given probability level, <span class="math inline">\(z_\alpha = \Phi^{-1}\left(\alpha\right)\)</span> be the associated quantile, and we record a number <span class="math inline">\(R_i^\alpha\)</span> defined as follows.</p> <p>If <span class="math inline">\(\alpha \leq 0.5\)</span>, <span class="math inline">\(R_\alpha^i\)</span> is the number of <span class="math inline">\(z\)</span> scores in row <span class="math inline">\(i\)</span> that are smaller than <span class="math inline">\(z_\alpha\)</span>; otherwise, if <span class="math inline">\(\alpha > 0.5\)</span>, <span class="math inline">\(R_\alpha^i\)</span> is the number of <span class="math inline">\(z\)</span> scores in row <span class="math inline">\(i\)</span> that are larger than <span class="math inline">\(z_\alpha\)</span>.</p> <p>Defined this way, <span class="math inline">\(R_\alpha^i\)</span> should be a sample from <span class="math inline">\(n \times F_n^{R_i}\left(z_\alpha\right)\)</span> or <span class="math inline">\(n \times \left(1- F_n^{R_i}\left(z_\alpha\right)\right)\)</span>. We can check if <span class="math inline">\(E\left[F_n\left(z\right)\right] = \Phi\left(z\right)\)</span> by looking at if the average <span class="math display">\[ \bar R_\alpha \approx \begin{cases} n\Phi\left(z_\alpha\right) = n\alpha & \alpha \leq 0.5 \\ n\left(1-\Phi\left(z_\alpha\right)\right) = n\left(1 - \alpha\right) & \alpha > 0.5\end{cases} \ . \]</span> We may also compare the frequencies of <span class="math inline">\(R_\alpha^i\)</span> with their theoretical expected values <span class="math inline">\(m \times \text{Binomial}\left(n, \alpha\right)\)</span> (in blue) assuming <span class="math inline">\(z_{ij}\)</span> are independent.</p> <p><img src="figure/marginal_z.rmd/unnamed-chunk-5-1.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-2.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-3.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-4.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-5.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-6.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-7.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-8.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-9.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-10.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-11.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-12.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-13.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-14.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-15.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-16.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-17.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-18.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-19.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-20.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-5-21.png" width="672" style="display: block; margin: auto;" /></p> <div id="independent-case-row-wise" class="section level3"> <h3>Independent case: row-wise</h3> <p><img src="figure/marginal_z.rmd/unnamed-chunk-6-1.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-2.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-3.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-4.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-5.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-6.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-7.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-8.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-9.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-10.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-11.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-12.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-13.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-14.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-15.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-16.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-17.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-18.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-19.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-20.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-6-21.png" width="672" style="display: block; margin: auto;" /></p> </div> </div> <div id="column-wise-closer-to-nleft0-1right" class="section level2"> <h2>Column-wise: closer to <span class="math inline">\(N\left(0, 1\right)\)</span></h2> <p>Each column of <span class="math inline">\(z\)</span> should be seen as <span class="math inline">\(z\)</span> scores of a non-differentially expressed gene in different data sets. Therefore, column-wise, the empirical distribution <span class="math inline">\(F_m^{C_j}\left(z\right)\)</span> should be closer to <span class="math inline">\(\Phi\left(z\right)\)</span> than <span class="math inline">\(F_m^{R_i}\left(z\right)\)</span>.</p> <p>Similarly, we are plotting <span class="math inline">\(C_\alpha^i\)</span>, compared with their theoretical frequencies as follows.</p> <p><img src="figure/marginal_z.rmd/unnamed-chunk-8-1.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-2.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-3.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-4.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-5.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-6.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-7.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-8.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-9.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-10.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-11.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-12.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-13.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-14.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-15.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-16.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-8-17.png" width="672" style="display: block; margin: auto;" /></p> <div id="independent-case-column-wise" class="section level3"> <h3>Independent case: column wise</h3> <p><img src="figure/marginal_z.rmd/unnamed-chunk-9-1.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-2.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-3.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-4.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-5.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-6.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-7.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-8.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-9.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-10.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-11.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-12.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-13.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-14.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-15.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-16.png" width="672" style="display: block; margin: auto;" /><img src="figure/marginal_z.rmd/unnamed-chunk-9-17.png" width="672" style="display: block; margin: auto;" /></p> </div> </div> <div id="conclusion" class="section level2"> <h2>Conclusion</h2> <p>The empirical distribution and the indicated marginal distribution of the correlated null <span class="math inline">\(z\)</span> scores are behaving not different from the expectation.</p> <p>Row-wise, the number of tail observations averages to what would be expected from correlated marginally <span class="math inline">\(N\left(0, 1\right)\)</span> random samples, validating Prof. Stein’s intuition.</p> <p>Column-wise, the distribution of the number of tail observations is closer to normal, closer to what would be expected under corelated marginally <span class="math inline">\(N\left(0, 1\right)\)</span>. Moreover, the distribution seems unimodal, and peaked at <span class="math inline">\(m\alpha\)</span> when <span class="math inline">\(\alpha \leq0.5\)</span> or <span class="math inline">\(m\left(1-\alpha\right)\)</span> when <span class="math inline">\(\alpha\geq0.5\)</span>. It suggests that the marginal distribution of the null <span class="math inline">\(z\)</span> scores for a certain gene is usually centered at <span class="math inline">\(0\)</span>, and more often than not, close to <span class="math inline">\(N\left(0, 1\right)\)</span>.</p> </div> <div id="session-information" class="section level2"> <h2>Session information</h2> <pre class="r"><code>sessionInfo()</code></pre> <pre><code>R version 3.4.3 (2017-11-30) Platform: x86_64-apple-darwin15.6.0 (64-bit) Running under: macOS High Sierra 10.13.4 Matrix products: default BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base loaded via a namespace (and not attached): [1] workflowr_1.0.1 Rcpp_0.12.16 digest_0.6.15 [4] rprojroot_1.3-2 R.methodsS3_1.7.1 backports_1.1.2 [7] git2r_0.21.0 magrittr_1.5 evaluate_0.10.1 [10] stringi_1.1.6 whisker_0.3-2 R.oo_1.21.0 [13] R.utils_2.6.0 rmarkdown_1.9 tools_3.4.3 [16] stringr_1.3.0 yaml_2.1.18 compiler_3.4.3 [19] htmltools_0.3.6 knitr_1.20 </code></pre> </div> <!-- Adjust MathJax settings so that all math formulae are shown using TeX fonts only; see http://docs.mathjax.org/en/latest/configuration.html. 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