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  133. <h1 id="seo-header">SingleR (二) 使用参考数据集预测分群</h1>
  134. <div class="markdown-body">
  135. <h2 id="第一步-构建-21-09-20-SingleR-R"><a href="#第一步-构建-21-09-20-SingleR-R" class="headerlink" title="第一步 构建 21.09.20.SingleR.R"></a>第一步 构建 21.09.20.SingleR.R</h2><figure class="highlight reasonml"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br><span class="line">76</span><br><span class="line">77</span><br><span class="line">78</span><br><span class="line">79</span><br><span class="line">80</span><br><span class="line">81</span><br><span class="line">82</span><br><span class="line">83</span><br><span class="line">84</span><br><span class="line">85</span><br><span class="line">86</span><br><span class="line">87</span><br><span class="line">88</span><br><span class="line">89</span><br><span class="line">90</span><br><span class="line">91</span><br><span class="line">92</span><br><span class="line">93</span><br><span class="line">94</span><br><span class="line">95</span><br><span class="line">96</span><br><span class="line">97</span><br><span class="line">98</span><br><span class="line">99</span><br><span class="line">100</span><br><span class="line">101</span><br><span class="line">102</span><br><span class="line">103</span><br><span class="line">104</span><br><span class="line">105</span><br><span class="line">106</span><br><span class="line">107</span><br><span class="line">108</span><br><span class="line">109</span><br><span class="line">110</span><br><span class="line">111</span><br><span class="line">112</span><br><span class="line">113</span><br><span class="line">114</span><br><span class="line">115</span><br><span class="line">116</span><br><span class="line">117</span><br><span class="line">118</span><br><span class="line">119</span><br><span class="line">120</span><br><span class="line">121</span><br><span class="line">122</span><br><span class="line">123</span><br><span class="line">124</span><br><span class="line">125</span><br><span class="line">126</span><br><span class="line">127</span><br><span class="line">128</span><br><span class="line">129</span><br><span class="line">130</span><br><span class="line">131</span><br><span class="line">132</span><br><span class="line">133</span><br></pre></td><td class="code"><pre><code class="hljs reasonml"># <span class="hljs-number">0</span>、加载程辑包<br>library(Seurat)<br>library(dplyr)<br>library(patchwork)<br><br># 加载 SingleR<br>library(SingleR)<br>library(SummarizedExperiment)<br>library(scater)<br>library(BiocParallel) # 并行计算加速<br><br># 配置数据路径<br>root_path = <span class="hljs-string">&quot;~/zlliu/R_data/21.07.15.IntegrateData&quot;</span><br><br># 配置结果保存路径<br>output_path = <span class="hljs-string">&quot;~/zlliu/R_output/21.09.20.SingleR&quot;</span><br><span class="hljs-keyword">if</span> (!file.exists(output_path))&#123;dir.create(output_path)&#125;<br><br># 设置工作目录,输出文件将保存在此目录下<br>setwd(output_path)<br>getwd<span class="hljs-literal">()</span><br><br># <span class="hljs-number">1</span>、读取数据和参考数据集<br>scRNAs = read<span class="hljs-constructor">RDS(<span class="hljs-params">file</span>.<span class="hljs-params">path</span>(<span class="hljs-params">root_path</span>, &#x27;<span class="hljs-params">hBLA_scRNAs</span>.<span class="hljs-params">rds</span>&#x27;)</span>)<br><span class="hljs-keyword">if</span> (!(<span class="hljs-string">&quot;hM1.se&quot;</span> %<span class="hljs-keyword">in</span>% ls<span class="hljs-literal">()</span>))&#123;<br> hM1.se &lt;- read<span class="hljs-constructor">RDS(<span class="hljs-string">&quot;/home/rqzhang/zlliu/R_data/human_M1_10x/hM1.se.rds&quot;</span>)</span><br>&#125;<br><span class="hljs-keyword">if</span> (!(<span class="hljs-string">&quot;hmca&quot;</span> %<span class="hljs-keyword">in</span>% ls<span class="hljs-literal">()</span>))&#123;<br> hmca &lt;- read<span class="hljs-constructor">RDS(<span class="hljs-string">&quot;/home/rqzhang/zlliu/R_data/Human_Multiple_Cortical_Areas_SMART-seq/hmca.rds&quot;</span>)</span><br>&#125;<br><br># <span class="hljs-number">1.1</span>、裁剪数据集<br>f_noNull &lt;- <span class="hljs-keyword">function</span>(lc_se, lc_col)&#123;<br> <span class="hljs-keyword">if</span>(any(lc_se$meta<span class="hljs-literal">[&quot;<span class="hljs-identifier">sample_name</span>&quot;]</span> != colnames(lc_se)))&#123;<br> return<br> &#125;<br> lc_idx = which(lc_se$meta<span class="hljs-literal">[<span class="hljs-identifier">lc_col</span>]</span><span class="hljs-operator"> == </span><span class="hljs-string">&quot;&quot;</span>)<br> lc_res = lc_se<span class="hljs-literal">[, -<span class="hljs-identifier">lc_idx</span>]</span><br> lc_res$meta = lc_se$meta<span class="hljs-literal">[-<span class="hljs-identifier">lc_idx</span>,]</span><br> lc_res<br>&#125;<br><br>hmca &lt;- f<span class="hljs-constructor">_noNull(<span class="hljs-params">hmca</span>, <span class="hljs-string">&quot;subclass_label&quot;</span>)</span><br><br># <span class="hljs-number">2</span>、构造预测方法<br>f_get_pred &lt;- <span class="hljs-keyword">function</span>(scRNA, lc_i)&#123;<br> <br> # 如果已经计算过了,就不再重复计算,直接返回上一次的结果<br> <span class="hljs-keyword">if</span>(file.exists(sprintf( <span class="hljs-string">&quot;%02d_hM1_subclass.txt&quot;</span>, lc_i)))&#123;<br> result_main_hpca &lt;- read.table(sprintf( <span class="hljs-string">&quot;%02d_hM1_subclass.txt&quot;</span>, lc_i), stringsAsFactors = F)<br> return (result_main_hpca)<br> &#125;<br> <br> # 导出原始counts矩阵<br> test.count=<span class="hljs-keyword">as</span>.data.frame(scRNA<span class="hljs-literal">[[&quot;RNA&quot;]</span>]@counts)<br> <br> # 保留共同基因<br> common_hpca &lt;- intersect(rownames(test.count), c(rownames(hM1.se), rownames(hmca)))<br> test.count_forhpca &lt;- test.count<span class="hljs-literal">[<span class="hljs-identifier">common_hpca</span>,]</span><br> tp_idx = na.omit(<span class="hljs-keyword">match</span>(common_hpca, rownames(hM1.se)))<br> lc_hM1.se &lt;- hM1.se<span class="hljs-literal">[<span class="hljs-identifier">rownames</span>(<span class="hljs-identifier">hM1</span>.<span class="hljs-identifier">se</span>)[<span class="hljs-identifier">tp_idx</span>]</span>, ]<br> tp_idx = na.omit(<span class="hljs-keyword">match</span>(common_hpca, rownames(hmca)))<br> lc_hmca &lt;- hmca<span class="hljs-literal">[<span class="hljs-identifier">rownames</span>(<span class="hljs-identifier">hmca</span>)[<span class="hljs-identifier">tp_idx</span>]</span>, ]<br><br> gc<span class="hljs-literal">()</span><br> <br> # 生成test数据集<br> test.count_forhpca.se &lt;- <span class="hljs-constructor">SummarizedExperiment(<span class="hljs-params">assays</span>=<span class="hljs-params">list</span>(<span class="hljs-params">counts</span>=<span class="hljs-params">test</span>.<span class="hljs-params">count_forhpca</span>)</span>)<br> test.count_forhpca.se &lt;- log<span class="hljs-constructor">NormCounts(<span class="hljs-params">test</span>.<span class="hljs-params">count_forhpca</span>.<span class="hljs-params">se</span>)</span><br> <br> # 进行分类预测 大概一小时<br> pred.main.hpca &lt;- <span class="hljs-constructor">SingleR(<span class="hljs-params">test</span> = <span class="hljs-params">test</span>.<span class="hljs-params">count_forhpca</span>.<span class="hljs-params">se</span>, <span class="hljs-params">ref</span> = <span class="hljs-params">list</span>(<span class="hljs-params">m1</span>=<span class="hljs-params">lc_hM1</span>.<span class="hljs-params">se</span>, <span class="hljs-params">mca</span>=<span class="hljs-params">lc_hmca</span>)</span>, labels = <span class="hljs-built_in">list</span>(hM1.se$meta$subclass_label, hmca$meta$subclass_label), BPPARAM=<span class="hljs-constructor">MulticoreParam(32)</span>) # <span class="hljs-number">32</span>CPUs<br><br> gc<span class="hljs-literal">()</span><br> <br> #构造返回结果<br> result_main_hpca &lt;- <span class="hljs-keyword">as</span>.data.frame(pred.main.hpca$labels)<br> result_main_hpca$CB &lt;- rownames(pred.main.hpca)<br> colnames(result_main_hpca) &lt;- c(&#x27;hM1_subclass&#x27;, &#x27;CB&#x27;)<br> write.table(result_main_hpca, sprintf( <span class="hljs-string">&quot;%02d_hM1_subclass.txt&quot;</span>, lc_i)) #保存下来,方便以后调用<br> result_main_hpca<br>&#125;<br><br># <span class="hljs-number">3</span>、进行预测<br>tp_sc &lt;- scRNAs<br># rm(x10s)<br>gc<span class="hljs-literal">()</span><br>tp_sc_st &lt;- <span class="hljs-number">1</span><br>tp_sc_len &lt;- length(tp_sc)<br><span class="hljs-keyword">for</span> (lc_i <span class="hljs-keyword">in</span> tp_sc_st:tp_sc_len) &#123;<br> f<span class="hljs-constructor">_get_pred(<span class="hljs-params">tp_sc</span>[[<span class="hljs-params">lc_i</span>]], <span class="hljs-params">lc_i</span>)</span><br>&#125;<br><br># <span class="hljs-number">4</span>、读取预测信息的函数<br>f_set_pred &lt;- <span class="hljs-keyword">function</span>(scRNA, result_main_hpca)&#123;<br> scRNA@meta.data$CB &lt;- rownames(scRNA@meta.data)<br># print(scRNA@meta.data$CB)<br> scRNA@meta.data=merge(scRNA@meta.data,result_main_hpca,by=<span class="hljs-string">&quot;CB&quot;</span>)<br># print(result_main_hpca$CB)<br> rownames(scRNA@meta.data)=scRNA@meta.data$CB<br> scRNA<br>&#125;<br><br><span class="hljs-keyword">for</span> (lc_i <span class="hljs-keyword">in</span> tp_sc_st:tp_sc_len) &#123;<br> tp_sc<span class="hljs-literal">[[<span class="hljs-identifier">lc_i</span>]</span>] &lt;- f<span class="hljs-constructor">_set_pred(<span class="hljs-params">tp_sc</span>[[<span class="hljs-params">lc_i</span>]], <span class="hljs-params">f_get_pred</span>(<span class="hljs-params">tp_sc</span>[[<span class="hljs-params">lc_i</span>]], <span class="hljs-params">lc_i</span>)</span>)<br>&#125;<br><br># <span class="hljs-number">5</span>、查找marker<br>f_findMarkers &lt;- <span class="hljs-keyword">function</span>(lc_scRNA, lc_group.by)&#123;<br> <span class="hljs-constructor">Idents(<span class="hljs-params">lc_scRNA</span>)</span> &lt;- lc_scRNA@meta.data<span class="hljs-literal">[,<span class="hljs-identifier">lc_group</span>.<span class="hljs-identifier">by</span>]</span><br> lc_markers &lt;- <span class="hljs-constructor">FindAllMarkers(<span class="hljs-params">lc_scRNA</span>, <span class="hljs-params">only</span>.<span class="hljs-params">pos</span> = TRUE, <span class="hljs-params">group</span>.<span class="hljs-params">by</span> = <span class="hljs-params">lc_group</span>.<span class="hljs-params">by</span>, <span class="hljs-params">min</span>.<span class="hljs-params">pct</span> = 0.25, <span class="hljs-params">logfc</span>.<span class="hljs-params">threshold</span> = 0.25)</span><br> lc_markers &lt;- subset(lc_markers, subset = p_val_adj&lt;<span class="hljs-number">0.05</span>)<br> lc_markers<br>&#125;<br><br>tp_markers &lt;- <span class="hljs-built_in">list</span><span class="hljs-literal">()</span><br><span class="hljs-keyword">for</span> (lc_i <span class="hljs-keyword">in</span> <span class="hljs-number">1</span>:length(tp_sc)) &#123;<br> tp_markers<span class="hljs-literal">[[<span class="hljs-identifier">lc_i</span>]</span>] &lt;- f<span class="hljs-constructor">_findMarkers(<span class="hljs-params">tp_sc</span>[[<span class="hljs-params">lc_i</span>]], &#x27;<span class="hljs-params">hM1_subclass</span>&#x27;)</span><br>&#125;<br><br>gl_MarkerGene &lt;- read.csv(file.path(<span class="hljs-string">&quot;~/zlliu/R_data/hBLA&quot;</span>, <span class="hljs-string">&quot;cellType_Markers.csv&quot;</span>), header = F)<br><br>f_matchKownMarker &lt;- <span class="hljs-keyword">function</span>(lc_markers_all, lc_markers_kown)&#123;<br> lc_CellType &lt;- lc_markers_kown<span class="hljs-literal">[<span class="hljs-identifier">match</span>(<span class="hljs-identifier">rownames</span>(<span class="hljs-identifier">lc_markers_all</span>), <span class="hljs-identifier">lc_markers_kown</span>[,<span class="hljs-number">1</span>]</span>),<span class="hljs-number">2</span>]<br> cbind(lc_markers_all, lc_CellType)<br>&#125;<br><br><span class="hljs-keyword">for</span> (lc_i <span class="hljs-keyword">in</span> <span class="hljs-number">1</span>:length(tp_sc)) &#123;<br> write.csv(f<span class="hljs-constructor">_matchKownMarker(<span class="hljs-params">tp_markers</span>[[<span class="hljs-params">lc_i</span>]], <span class="hljs-params">gl_MarkerGene</span>)</span>, sprintf( <span class="hljs-string">&quot;%02d_significant_markers_%s.csv&quot;</span>, lc_i, names(tp_sc)<span class="hljs-literal">[<span class="hljs-identifier">lc_i</span>]</span>))<br>&#125;<br><br>gl_MarkerGene &lt;- read.csv(<span class="hljs-string">&quot;~/zlliu/R_data/hBLA/TableS3.csv&quot;</span>, header = T)<br><br></code></pre></td></tr></table></figure>
  136. <h2 id="第二步-构建-21-09-20-SingleR-pbs-并提交"><a href="#第二步-构建-21-09-20-SingleR-pbs-并提交" class="headerlink" title="第二步 构建 21.09.20.SingleR.pbs 并提交"></a>第二步 构建 21.09.20.SingleR.pbs 并提交</h2><figure class="highlight gradle"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><code class="hljs gradle">#!<span class="hljs-regexp">/bin/</span>bash<br>#PBS -q fat<br>#PBS -V<br>#PBS -o <span class="hljs-regexp">/home/</span>rqzhang<span class="hljs-regexp">/zlliu/</span>PBS<span class="hljs-regexp">/SingleR/</span>SingleR.out<br>#PBS -e <span class="hljs-regexp">/home/</span>rqzhang<span class="hljs-regexp">/zlliu/</span>PBS<span class="hljs-regexp">/SingleR/</span>SingleR.err<br>#PBS -l nodes=<span class="hljs-number">1</span>:ppn=<span class="hljs-number">32</span><br>#PBS -r y<br>cd <span class="hljs-regexp">/home/</span>rqzhang<br>Rscript <span class="hljs-regexp">/home/</span>rqzhang<span class="hljs-regexp">/zlliu/</span>PBS<span class="hljs-regexp">/SingleR/</span><span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x.hM1.se.R<br>echo $HOME<br></code></pre></td></tr></table></figure>
  137. <ul>
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  392. <div class="noscript-warning">Blog works best with JavaScript enabled</div>
  393. </noscript>
  394. <!-- hexo injector body_end start -->
  395. <script defer src="/theme-inject/timeliness.js"></script>
  396. <!-- hexo injector body_end end --></body>
  397. </html>