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            <h1 id="seo-header">SingleR (二) 使用参考数据集预测分群</h1>
            
            
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                <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 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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>

<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>

<ul>
<li>提交job：<code>qsub /home/rqzhang/zlliu/PBS/SingleR/21.09.20.SingleR.pbs</code></li>
<li>查看所有任务：<code>qstat</code></li>
</ul>

                
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