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            <h1 id="seo-header">复旦高性能计算 (二) qsub使用方法</h1>
            
            
              <div class="markdown-body">
                
                <h2 id="管理使用"><a href="#管理使用" class="headerlink" title="管理使用"></a>管理使用</h2><ul>
<li>查看所有任务：<code>qstat</code></li>
<li>删除某个任务：<code>qdel &lt;Job ID&gt;</code></li>
<li>交互使用：<code>qsub -I [-q &lt;batch&gt;]</code></li>
<li>登入指定节点：<code>qsub -l nodes=cu05 -I</code></li>
</ul>
<h2 id="提交任务"><a href="#提交任务" class="headerlink" title="提交任务"></a>提交任务</h2><h3 id="示例一-jupyter-pbs"><a href="#示例一-jupyter-pbs" class="headerlink" title="示例一 jupyter.pbs"></a>示例一 <code>jupyter.pbs</code></h3><ul>
<li>创建 <code>/home/rqzhang/jupyter.pbs</code> 写入以下内容：</li>
</ul>
<figure class="highlight bash"><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></pre></td><td class="code"><pre><code class="hljs bash"><span class="hljs-meta">#!/bin/bash</span><br><span class="hljs-comment">#PBS -q batch</span><br><span class="hljs-comment">#PBS -V</span><br><span class="hljs-comment">#PBS -o /home/rqzhang/jupyter.out</span><br><span class="hljs-comment">#PBS -e /home/rqzhang/jupyter.err</span><br><span class="hljs-comment">#PBS -l nodes=1:ppn=8</span><br><span class="hljs-comment">#PBS -r y</span><br><span class="hljs-built_in">cd</span> /home/rqzhang<br>/home/rqzhang/zlliu/bin/frpc -c /home/rqzhang/zlliu/frp/frpc.ini &amp;<br>jupyter notebook --ip=<span class="hljs-string">&#x27;0.0.0.0&#x27;</span> --port=18888 --no-browser --NotebookApp.token=<span class="hljs-string">&quot;&lt;token&gt;&quot;</span> --NotebookNotary.db_file=<span class="hljs-string">&#x27;:memory:&#x27;</span><br><span class="hljs-built_in">echo</span> <span class="hljs-variable">$HOME</span><br></code></pre></td></tr></table></figure>

<ul>
<li>提交任务： <code>qsub ./jupyter.pbs</code></li>
</ul>
<h3 id="示例二-SingleR-pbs"><a href="#示例二-SingleR-pbs" class="headerlink" title="示例二 SingleR.pbs"></a>示例二 <code>SingleR.pbs</code></h3><ul>
<li>创建 <code>/home/rqzhang/`SingleR.pbs` </code> 写入以下内容：</li>
</ul>
<figure class="highlight bash"><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 bash"><span class="hljs-meta">#!/bin/bash</span><br><span class="hljs-comment">#PBS -q fat</span><br><span class="hljs-comment">#PBS -V</span><br><span class="hljs-comment">#PBS -o /home/rqzhang/SingleR.out</span><br><span class="hljs-comment">#PBS -e /home/rqzhang/SingleR.err</span><br><span class="hljs-comment">#PBS -l nodes=1:ppn=32</span><br><span class="hljs-comment">#PBS -r y</span><br><span class="hljs-built_in">cd</span> /home/rqzhang<br>Rscript /home/rqzhang/r.pbs/21.07.15.10x.hM1.se.R<br><span class="hljs-built_in">echo</span> <span class="hljs-variable">$HOME</span><br></code></pre></td></tr></table></figure>

<ul>
<li>创建 <code>/home/rqzhang/r.pbs/21.07.15.10x.hM1.se.R</code> 写入以下内容：</li>
</ul>
<figure class="highlight mipsasm"><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></pre></td><td class="code"><pre><code class="hljs mipsasm"><span class="hljs-comment"># 0、加载程辑包</span><br>library(Seurat)<br>library(dplyr)<br>library(patchwork)<br><br><span class="hljs-comment"># 配置数据和mark基因表的路径</span><br>root_path = <span class="hljs-string">&quot;~/zlliu/R_data/hBLA&quot;</span><br><span class="hljs-comment"># 配置结果保存路径</span><br>output_path = <span class="hljs-string">&quot;~/zlliu/R_output/21.07.15.10x.hM1.se/&quot;</span><br><br><span class="hljs-comment"># 设置工作目录，输出文件将保存在此目录下</span><br>setwd(output_path)<br>print(getwd())<br><br><span class="hljs-comment"># 5、读取全部samples</span><br>tp_samples &lt;- list.files(file.path(root_path, <span class="hljs-string">&quot;10x&quot;</span>))<br>tp_dir &lt;- file.path(root_path, <span class="hljs-string">&quot;10x&quot;</span>, tp_samples)<br>names(tp_dir) &lt;- tp_samples<br>counts &lt;- Read10X(data.<span class="hljs-keyword">dir </span>= tp_dir)<br><span class="hljs-keyword">scRNA </span>&lt;- CreateSeuratObject(counts, project = <span class="hljs-string">&#x27;hBLA&#x27;</span>,<br>                            min.cells = <span class="hljs-number">3</span>, min.features = <span class="hljs-number">200</span>)<br>rm(counts)<br>rm(tp_dir)<br>gc()<br><br><span class="hljs-comment"># 6、QC</span><br><span class="hljs-keyword">scRNA[[&quot;percent.mt&quot;]] </span>&lt;- PercentageFeatureSet(<span class="hljs-keyword">scRNA, </span>pattern = <span class="hljs-string">&quot;^MT-&quot;</span>)<br><br><span class="hljs-comment"># 6.2、分割数据以便QC</span><br>x10s &lt;- SplitObject(<span class="hljs-keyword">scRNA, </span>split.<span class="hljs-keyword">by </span>= <span class="hljs-string">&#x27;ident&#x27;</span>)<br>rm(<span class="hljs-keyword">scRNA)</span><br><span class="hljs-keyword"></span>gc()<br><br><span class="hljs-comment"># 6.3、分别对各样本进行QC</span><br>x10s$<span class="hljs-keyword">BA213 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA213,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">4000</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA04 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA04,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">3000</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA09 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA09,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">3500</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA21 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA21,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">4500</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA22 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA22,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">3000</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA39 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA39,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">4000</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA40 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA40,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">4000</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA44 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA44,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">4000</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br>x10s$<span class="hljs-keyword">BA45 </span>&lt;- <span class="hljs-keyword">subset(x10s$BA45,</span><br><span class="hljs-keyword"></span>                  <span class="hljs-keyword">subset </span>= nFeature_RNA &gt; <span class="hljs-number">200</span> &amp; nFeature_RNA &lt; <span class="hljs-number">5000</span> &amp; percent.mt &lt; <span class="hljs-number">10</span>)<br><br><span class="hljs-comment"># 加载 SingleR</span><br>library(SingleR)<br>library(SummarizedExperiment)<br>library(<span class="hljs-keyword">scater)</span><br><span class="hljs-keyword"></span>library(<span class="hljs-keyword">BiocParallel) </span><span class="hljs-comment"># 并行计算加速</span><br><br><span class="hljs-comment"># 加载参考数据集 大概3分钟</span><br>if (!(<span class="hljs-string">&quot;hM1.se&quot;</span> %in% ls()))&#123;<br>    hM1.se &lt;- readRDS(<span class="hljs-string">&quot;/home/rqzhang/zlliu/R_data/human_M1_10x/hM1.se.rds&quot;</span>)<br>&#125;<br><br>f_get_pred &lt;- function(<span class="hljs-keyword">scRNA, </span>lc_i)&#123;<br>    <br>    <span class="hljs-comment"># 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</span><br>    if(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>    <span class="hljs-comment"># 导出原始counts矩阵</span><br>    test.count=as<span class="hljs-meta">.data</span>.frame(<span class="hljs-keyword">scRNA[[&quot;RNA&quot;]]@counts)</span><br><span class="hljs-keyword"></span>    <br>    <span class="hljs-comment"># 保留共同基因</span><br>    common_hpca &lt;- intersect(rownames(test.count), rownames(hM1.se))<br>    lc_hM1.se &lt;- hM1.se[common_hpca,]<br>    test.count_forhpca &lt;- test.count[common_hpca,]<br>    gc()<br>    <br>    <span class="hljs-comment"># 生成test数据集</span><br>    test.count_forhpca.se &lt;- SummarizedExperiment(assays=list(counts=test.count_forhpca))<br>    test.count_forhpca.se &lt;- logNormCounts(test.count_forhpca.se)<br>    <br>    <span class="hljs-comment"># 进行分类预测 大概一小时</span><br>    pred.main.hpca &lt;- SingleR(test = test.count_forhpca.se, ref = lc_hM1.se, labels = hM1.se$meta$<span class="hljs-keyword">subclass_label, </span><span class="hljs-keyword">BPPARAM=MulticoreParam(32))</span><br><span class="hljs-keyword"></span>    <span class="hljs-comment"># 32 CPUs</span><br>    gc()<br>    <br>    <span class="hljs-comment">#构造返回结果</span><br>    result_main_hpca &lt;- as<span class="hljs-meta">.data</span>.frame(pred.main.hpca$labels)<br>    result_main_hpca$CB &lt;- rownames(pred.main.hpca)<br>    colnames(result_main_hpca) &lt;- c(<span class="hljs-string">&#x27;hM1_subclass&#x27;</span>, <span class="hljs-string">&#x27;CB&#x27;</span>)<br>    write.table(result_main_hpca, sprintf( <span class="hljs-string">&quot;%02d_hM1_subclass.txt&quot;</span>, lc_i)) <span class="hljs-comment">#保存下来，方便以后调用</span><br>    result_main_hpca<br>&#125;<br><br>tp_sc &lt;- x10s<br><span class="hljs-comment"># rm(x10s)</span><br>gc()<br>tp_sc_st &lt;- <span class="hljs-number">1</span><br>tp_sc_len &lt;- length(tp_sc)<br>for (lc_i in tp_sc_st:tp_sc_len) &#123;<br>    print(lc_i)<br>    f_get_pred(tp_sc[[lc_i]], lc_i)<br>&#125;<br></code></pre></td></tr></table></figure>

<ul>
<li>提交任务： <code>qsub ./`` `SingleR.pbs` `` </code></li>
</ul>
<h3 id="示例三-cellphonedb-pbs"><a href="#示例三-cellphonedb-pbs" class="headerlink" title="示例三 cellphonedb.pbs"></a>示例三 <code>cellphonedb.pbs</code></h3><ul>
<li>创建 <code>/home/rqzhang/`cellphonedb.pbs` </code> 写入以下内容：</li>
</ul>
<figure class="highlight stylus"><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></pre></td><td class="code"><pre><code class="hljs stylus">#!/bin/bash<br><span class="hljs-selector-id">#PBS</span> -<span class="hljs-selector-tag">q</span> fat<br><span class="hljs-selector-id">#PBS</span> -V<br><span class="hljs-selector-id">#PBS</span> -o /home/rqzhang/cellphonedb<span class="hljs-selector-class">.out</span><br><span class="hljs-selector-id">#PBS</span> -e /home/rqzhang/cellphonedb<span class="hljs-selector-class">.err</span><br><span class="hljs-selector-id">#PBS</span> -l nodes=<span class="hljs-number">1</span>:ppn=<span class="hljs-number">32</span><br><span class="hljs-selector-id">#PBS</span> -r y<br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_01<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_02<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_03<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_04<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_05<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_06<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_07<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_08<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>cd /home/rqzhang/zlliu/R_output/<span class="hljs-number">21.07</span>.<span class="hljs-number">15.10</span>x<span class="hljs-selector-class">.hM1</span>.se/SingleR_09<br>cellphonedb method statistical_analysis  cellphonedb_meta<span class="hljs-selector-class">.txt</span>  cellphonedb_count<span class="hljs-selector-class">.txt</span> <span class="hljs-attr">--counts-data</span>=gene_name  <span class="hljs-attr">--threads</span>=<span class="hljs-number">32</span><br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta<span class="hljs-selector-class">.txt</span><br><br>echo <span class="hljs-variable">$HOME</span><br></code></pre></td></tr></table></figure>

<ul>
<li>提交任务： <code>qsub ./```` ``` `` `cellphonedb.pbs` `` ``` ```` </code></li>
</ul>

                
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