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- <h2 id="重命名R1、R2">重命名R1、R2</h2>
- <ul>
- <li><a href="/shi-yong-GATK-zhao-SNP#fastp%E4%B8%80%E9%94%AE%E8%B4%A8%E6%8E%A7">原始数据质控</a></li>
- </ul>
- <h3 id="重命名前">重命名前</h3>
- <p>├── SRR12391722<br>
- │ ├── SRR12391722_1.fastq.gz<br>
- │ └── SRR12391722_2.fastq.gz<br>
- ├── SRR12391723<br>
- │ ├── SRR12391723_1.fastq.gz<br>
- │ └── SRR12391723_2.fastq.gz<br>
- ├── SRR12391724<br>
- │ ├── SRR12391724_1.fastq.gz<br>
- │ └── SRR12391724_2.fastq.gz<br>
- └── SRR12391725<br>
- │├── SRR12391725_1.fastq.gz<br>
- │└── SRR12391725_2.fastq.gz</p>
- <h3 id="重命名后">重命名后</h3>
- <p>SRX8890106<br>
- ├── SRX8890106_S1_L001_R1_001.fastq.gz<br>
- ├── SRX8890106_S1_L001_R2_001.fastq.gz<br>
- ├── SRX8890106_S1_L002_R1_001.fastq.gz<br>
- ├── SRX8890106_S1_L002_R2_001.fastq.gz<br>
- ├── SRX8890106_S1_L003_R1_001.fastq.gz<br>
- ├── SRX8890106_S1_L003_R2_001.fastq.gz<br>
- ├── SRX8890106_S1_L004_R1_001.fastq.gz<br>
- └── SRX8890106_S1_L004_R2_001.fastq.gz</p>
- <h2 id="进行定量">进行定量</h2>
- <p><a target="_blank" rel="noopener" href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/tutorial_ct">Running cellranger count</a>; <a target="_blank" rel="noopener" href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/installation">cellranger 安装</a></p>
- <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><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></pre></td><td class="code"><pre><span class="line"><span class="meta">#!/bin/bash</span></span><br><span class="line"><span class="built_in">export</span> PATH=/opt/cellranger/cellranger-6.1.2:<span class="variable">$PATH</span></span><br><span class="line">db=/opt/cellranger/refdata-gex-GRCh38-2020-A</span><br><span class="line">data=/home/jovyan/work_st/sce/GSE137829/data</span><br><span class="line">work=/home/jovyan/work_st/sce/GSE137829/res</span><br><span class="line"><span class="built_in">mkdir</span> <span class="variable">$work</span></span><br><span class="line"><span class="built_in">cd</span> <span class="variable">$work</span></span><br><span class="line"><span class="keyword">for</span> sample <span class="keyword">in</span> <span class="variable">${data}</span>/*;</span><br><span class="line"><span class="keyword">do</span></span><br><span class="line"><span class="built_in">echo</span> <span class="variable">$sample</span></span><br><span class="line">sample_res=<span class="variable">${sample##*/}</span></span><br><span class="line">cellranger count --<span class="built_in">id</span>=<span class="variable">$sample_res</span> \</span><br><span class="line">--localcores=12 \</span><br><span class="line">--transcriptome=<span class="variable">$db</span> \</span><br><span class="line">--fastqs=<span class="variable">$sample</span> \</span><br><span class="line">--sample=<span class="variable">$sample_res</span> \</span><br><span class="line">--expect-cells=5000</span><br><span class="line"><span class="keyword">done</span></span><br></pre></td></tr></table></figure>
- <ul>
- <li>nano <a target="_blank" rel="noopener" href="http://103.sh">103.sh</a></li>
- <li>chmod +x <a target="_blank" rel="noopener" href="http://103.sh">103.sh</a></li>
- <li>./103.sh</li>
- </ul>
- <h2 id="附加:scVelo-细胞轨迹">附加:scVelo 细胞轨迹</h2>
- <h3 id="安装依赖">安装依赖</h3>
- <h4 id="cellranger">cellranger</h4>
- <p>GRCh38_rmsk.gtf.gz:<a target="_blank" rel="noopener" href="https://genome.ucsc.edu/cgi-bin/hgTables?hgsid=611454127_NtvlaW6xBSIRYJEBI0iRDEWisITa&clade=mammal&org=Human&db=0&hgta_group=allTracks&hgta_track=rmsk&hgta_table=rmsk&hgta_regionType=genome&position=&hgta_outputType=gff&hgta_outFileName=GRCh38_rmsk.gtf">https://genome.ucsc.edu/cgi-bin/hgTables</a></p>
- <p><img src="https://img.limour.top/2023/09/01/64f1cf9a391ae.webp" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt=""></p>
- <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><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br></pre></td><td class="code"><pre><span class="line"><span class="built_in">cd</span> /opt/cellranger</span><br><span class="line">wget <Cell Ranger></span><br><span class="line">wget <References></span><br><span class="line">tar -xzvf cellranger-6.1.2.tar.gz</span><br><span class="line">tar -xzvf refdata-gex-GRCh38-2020-A.tar.gz</span><br><span class="line">下载 GRCh38_rmsk.gtf.gz 上传阿里云盘</span><br><span class="line">./aliyunpan</span><br><span class="line">login</span><br><span class="line">d GRCh38_rmsk.gtf.gz -saveto /opt/cellranger</span><br><span class="line">gunzip GRCh38_rmsk.gtf.gz</span><br><span class="line"><span class="built_in">export</span> PATH=/opt/cellranger/cellranger-6.1.2:<span class="variable">$PATH</span></span><br><span class="line">cellranger sitecheck > sitecheck.txt</span><br><span class="line">cellranger upload xxx@fudan.edu.cn sitecheck.txt</span><br><span class="line">cellranger testrun --<span class="built_in">id</span>=tiny</span><br><span class="line">cellranger upload xxx@fudan.edu.cn tiny/tiny.mri.tgz</span><br></pre></td></tr></table></figure>
- <h4 id="velocyto">velocyto</h4>
- <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></pre></td><td class="code"><pre><span class="line">conda create -n velocyto -c conda-forge python=3.7 -y</span><br><span class="line">conda activate velocyto</span><br><span class="line">conda install numpy scipy cython numba matplotlib scikit-learn h5py click -y</span><br><span class="line">pip install pysam</span><br><span class="line">pip install velocyto</span><br><span class="line">velocyto --<span class="built_in">help</span></span><br><span class="line">conda install -c bioconda samtools=1.15.1 -y</span><br></pre></td></tr></table></figure>
- <h4 id="scVelo">scVelo</h4>
- <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><span class="line">conda install -c conda-forge widgetsnbextension -y</span><br><span class="line">jupyter nbextension <span class="built_in">enable</span> --py widgetsnbextension</span><br><span class="line"><span class="comment"># 重启 jupyter</span></span><br><span class="line">conda create -n scVelo -c conda-forge python=3.7 -y</span><br><span class="line">conda activate scVelo</span><br><span class="line">conda install -c conda-forge scanpy -y</span><br><span class="line">conda install -c conda-forge matplotlib -y</span><br><span class="line">pip install -U scvelo</span><br><span class="line">pip install -U tqdm ipywidgets</span><br><span class="line">conda install -c conda-forge ipykernel -y</span><br><span class="line">python -m ipykernel install --user --name python-scVelo</span><br></pre></td></tr></table></figure>
- <h3 id="准备1:运行-cellranger">准备1:运行 cellranger</h3>
- <p>data<br>
- ├── hPB003<br>
- │ ├── hPB003_S1_L001_R1_001.fastq.gz<br>
- │ └── hPB003_S1_L001_R2_001.fastq.gz<br>
- ├── hPB004<br>
- │ ├── hPB004_S1_L001_R1_001.fastq.gz<br>
- │ └── hPB004_S1_L001_R2_001.fastq.gz<br>
- ├── hPB005<br>
- │ ├── hPB005_S1_L001_R1_001.fastq.gz<br>
- │ └── hPB005_S1_L001_R2_001.fastq.gz<br>
- ├── hPB006<br>
- │ ├── hPB006_S1_L001_R1_001.fastq.gz<br>
- │ └── hPB006_S1_L001_R2_001.fastq.gz<br>
- └── hPB007<br>
- ├── hPB007_S1_L001_R1_001.fastq.gz<br>
- └── hPB007_S1_L001_R2_001.fastq.gz</p>
- <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><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></pre></td><td class="code"><pre><span class="line"><span class="meta">#!/bin/bash</span></span><br><span class="line"><span class="built_in">export</span> PATH=/opt/cellranger/cellranger-6.1.2:<span class="variable">$PATH</span></span><br><span class="line">db=/opt/cellranger/refdata-gex-GRCh38-2020-A</span><br><span class="line">data=/home/jovyan/upload/zl_liu/data/data/data</span><br><span class="line">work=/home/jovyan/upload/zl_liu/data/data/res</span><br><span class="line"><span class="built_in">mkdir</span> <span class="variable">$work</span></span><br><span class="line"><span class="built_in">cd</span> <span class="variable">$work</span></span><br><span class="line"><span class="keyword">for</span> sample <span class="keyword">in</span> <span class="variable">${data}</span>/*;</span><br><span class="line"><span class="keyword">do</span> <span class="built_in">echo</span> <span class="variable">$sample</span></span><br><span class="line">sample_res=<span class="variable">${sample##*/}</span></span><br><span class="line">cellranger count --<span class="built_in">id</span>=<span class="variable">$sample_res</span> \</span><br><span class="line">--localcores=4 \</span><br><span class="line">--transcriptome=<span class="variable">$db</span> \</span><br><span class="line">--fastqs=<span class="variable">$sample</span> \</span><br><span class="line">--sample=<span class="variable">$sample_res</span> \</span><br><span class="line">--expect-cells=5000</span><br><span class="line"><span class="keyword">done</span></span><br></pre></td></tr></table></figure>
- <h3 id="准备2:从cellranger得到loom文件">准备2:从cellranger得到loom文件</h3>
- <figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br></pre></td><td class="code"><pre><span class="line">conda activate velocyto</span><br><span class="line"><span class="comment">#!/bin/bash</span></span><br><span class="line">db=/opt/cellranger/refdata-gex-GRCh38-2020-A</span><br><span class="line">work=/home/jovyan/upload/zl_liu/data/data/res</span><br><span class="line">rmsk_gtf=/opt/cellranger/GRCh38_rmsk.gtf <span class="comment"># 从genome.ucsc.edu下载 </span></span><br><span class="line">cellranger_gtf=<span class="variable">${db}</span>/genes/genes.gtf</span><br><span class="line"><span class="built_in">ls</span> -lh <span class="variable">$rmsk_gtf</span> <span class="variable">$work</span> <span class="variable">$cellranger_gtf</span></span><br><span class="line"><span class="keyword">for</span> sample <span class="keyword">in</span> <span class="variable">${work}</span>/*;</span><br><span class="line"><span class="keyword">do</span> <span class="built_in">echo</span> <span class="variable">$sample</span></span><br><span class="line">velocyto run10x -m <span class="variable">$rmsk_gtf</span> <span class="variable">$sample</span> <span class="variable">$cellranger_gtf</span></span><br><span class="line"><span class="keyword">done</span></span><br></pre></td></tr></table></figure>
- <h3 id="准备3:从-Seurat-输出-标注-和-UMAP">准备3:从 Seurat 输出 标注 和 UMAP</h3>
- <figure class="highlight r"><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></pre></td><td class="code"><pre><span class="line">library<span class="punctuation">(</span>Seurat<span class="punctuation">)</span></span><br><span class="line">library<span class="punctuation">(</span>tidyverse<span class="punctuation">)</span></span><br><span class="line">library<span class="punctuation">(</span>stringr<span class="punctuation">)</span></span><br><span class="line">sce <span class="operator"><-</span> readRDS<span class="punctuation">(</span><span class="string">"~/upload/zl_liu/data/pca.rds"</span><span class="punctuation">)</span></span><br></pre></td></tr></table></figure>
- <figure class="highlight r"><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></pre></td><td class="code"><pre><span class="line">f_scVelo_group_by <span class="operator"><-</span> <span class="keyword">function</span><span class="punctuation">(</span>df<span class="punctuation">,</span> groupN<span class="punctuation">)</span><span class="punctuation">{</span></span><br><span class="line"> res <span class="operator"><-</span> <span class="built_in">list</span><span class="punctuation">(</span><span class="punctuation">)</span></span><br><span class="line"> <span class="keyword">for</span><span class="punctuation">(</span>n <span class="keyword">in</span> unique<span class="punctuation">(</span><span class="built_in">as.character</span><span class="punctuation">(</span>df<span class="punctuation">[[</span>groupN<span class="punctuation">]</span><span class="punctuation">]</span><span class="punctuation">)</span><span class="punctuation">)</span><span class="punctuation">)</span><span class="punctuation">{</span></span><br><span class="line"> res<span class="punctuation">[[</span>n<span class="punctuation">]</span><span class="punctuation">]</span> <span class="operator"><-</span> df<span class="punctuation">[</span>df<span class="punctuation">[[</span>groupN<span class="punctuation">]</span><span class="punctuation">]</span> <span class="operator">==</span> n<span class="punctuation">,</span><span class="punctuation">]</span></span><br><span class="line"> <span class="punctuation">}</span></span><br><span class="line"> res</span><br><span class="line"><span class="punctuation">}</span></span><br><span class="line">f_scVelo_get_reduction <span class="operator"><-</span> <span class="keyword">function</span><span class="punctuation">(</span>dfl<span class="punctuation">,</span> cell.embeddings<span class="punctuation">)</span><span class="punctuation">{</span></span><br><span class="line"> <span class="keyword">for</span><span class="punctuation">(</span>n <span class="keyword">in</span> <span class="built_in">names</span><span class="punctuation">(</span>dfl<span class="punctuation">)</span><span class="punctuation">)</span><span class="punctuation">{</span></span><br><span class="line"> dfl<span class="punctuation">[[</span>n<span class="punctuation">]</span><span class="punctuation">]</span> <span class="operator"><-</span> cbind<span class="punctuation">(</span>dfl<span class="punctuation">[[</span>n<span class="punctuation">]</span><span class="punctuation">]</span><span class="punctuation">,</span> cell.embeddings<span class="punctuation">[</span>rownames<span class="punctuation">(</span>dfl<span class="punctuation">[[</span>n<span class="punctuation">]</span><span class="punctuation">]</span><span class="punctuation">)</span><span class="punctuation">,</span><span class="punctuation">]</span><span class="punctuation">)</span></span><br><span class="line"> <span class="punctuation">}</span></span><br><span class="line"> dfl</span><br><span class="line"><span class="punctuation">}</span></span><br><span class="line">f_scVelo_str_extract_rowN <span class="operator"><-</span> <span class="keyword">function</span><span class="punctuation">(</span>dfl<span class="punctuation">,</span> grepP<span class="operator">=</span><span class="string">'(?=.{10})([AGCT]{16})(?=-1)'</span><span class="punctuation">)</span><span class="punctuation">{</span></span><br><span class="line"> <span class="keyword">for</span><span class="punctuation">(</span>n <span class="keyword">in</span> <span class="built_in">names</span><span class="punctuation">(</span>dfl<span class="punctuation">)</span><span class="punctuation">)</span><span class="punctuation">{</span></span><br><span class="line"> rownames<span class="punctuation">(</span>dfl<span class="punctuation">[[</span>n<span class="punctuation">]</span><span class="punctuation">]</span><span class="punctuation">)</span> <span class="operator"><-</span> str_extract<span class="punctuation">(</span>rownames<span class="punctuation">(</span>dfl<span class="punctuation">[[</span>n<span class="punctuation">]</span><span class="punctuation">]</span><span class="punctuation">)</span><span class="punctuation">,</span> grepP<span class="punctuation">)</span></span><br><span class="line"> <span class="punctuation">}</span></span><br><span class="line"> dfl</span><br><span class="line"><span class="punctuation">}</span></span><br><span class="line"></span><br><span class="line">test <span class="operator"><-</span> f_scVelo_group_by<span class="punctuation">(</span>sce<span class="punctuation">[[</span><span class="built_in">c</span><span class="punctuation">(</span><span class="string">'patient_id'</span><span class="punctuation">,</span><span class="string">'cell_type_fig3'</span><span class="punctuation">)</span><span class="punctuation">]</span><span class="punctuation">]</span><span class="punctuation">,</span> <span class="string">'patient_id'</span><span class="punctuation">)</span></span><br><span class="line">test <span class="operator"><-</span> f_scVelo_get_reduction<span class="punctuation">(</span>test<span class="punctuation">,</span> sce<span class="operator">@</span>reductions<span class="operator">$</span>umap<span class="operator">@</span>cell.embeddings<span class="punctuation">)</span></span><br><span class="line">test <span class="operator"><-</span> f_scVelo_get_reduction<span class="punctuation">(</span>test<span class="punctuation">,</span> sce<span class="operator">@</span>reductions<span class="operator">$</span>pca<span class="operator">@</span>cell.embeddings<span class="punctuation">)</span></span><br><span class="line">test <span class="operator"><-</span> f_scVelo_str_extract_rowN<span class="punctuation">(</span>test<span class="punctuation">)</span></span><br></pre></td></tr></table></figure>
- <figure class="highlight r"><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><span class="line">f_scVelo_label_reduction <span class="operator"><-</span> <span class="keyword">function</span><span class="punctuation">(</span>dfl<span class="punctuation">,</span> workdir<span class="punctuation">,</span> groupN<span class="punctuation">,</span> outDir<span class="punctuation">)</span><span class="punctuation">{</span></span><br><span class="line"> outDir <span class="operator">=</span> file.path<span class="punctuation">(</span>workdir<span class="punctuation">,</span> outDir<span class="punctuation">,</span> <span class="string">'velocyto'</span><span class="punctuation">,</span> <span class="string">'metadata.csv'</span><span class="punctuation">)</span></span><br><span class="line"> write.csv<span class="punctuation">(</span>dfl<span class="punctuation">[[</span>groupN<span class="punctuation">]</span><span class="punctuation">]</span><span class="punctuation">,</span> outDir<span class="punctuation">)</span></span><br><span class="line"><span class="punctuation">}</span></span><br><span class="line"></span><br><span class="line">work<span class="operator">=</span><span class="string">'/home/jovyan/upload/zl_liu/data/data/res'</span></span><br><span class="line">f_scVelo_label_reduction<span class="punctuation">(</span>test<span class="punctuation">,</span> work<span class="punctuation">,</span> <span class="string">'patient1'</span><span class="punctuation">,</span> <span class="string">'hPB003'</span><span class="punctuation">)</span></span><br><span class="line">f_scVelo_label_reduction<span class="punctuation">(</span>test<span class="punctuation">,</span> work<span class="punctuation">,</span> <span class="string">'patient3'</span><span class="punctuation">,</span> <span class="string">'hPB004'</span><span class="punctuation">)</span></span><br><span class="line">f_scVelo_label_reduction<span class="punctuation">(</span>test<span class="punctuation">,</span> work<span class="punctuation">,</span> <span class="string">'patient4'</span><span class="punctuation">,</span> <span class="string">'hPB006'</span><span class="punctuation">)</span></span><br><span class="line">f_scVelo_label_reduction<span class="punctuation">(</span>test<span class="punctuation">,</span> work<span class="punctuation">,</span> <span class="string">'patient5'</span><span class="punctuation">,</span> <span class="string">'hPB007'</span><span class="punctuation">)</span></span><br></pre></td></tr></table></figure>
- <h3 id="运行1-合并数据">运行1: 合并数据</h3>
- <h4 id="第一步-导入模块">第一步 导入模块</h4>
- <figure class="highlight python"><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></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> scvelo <span class="keyword">as</span> scv</span><br><span class="line"><span class="keyword">import</span> scanpy <span class="keyword">as</span> sc</span><br><span class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</span><br><span class="line"><span class="keyword">import</span> pandas <span class="keyword">as</span> pd</span><br><span class="line"><span class="keyword">import</span> seaborn <span class="keyword">as</span> sns </span><br><span class="line">scv.settings.verbosity = <span class="number">3</span> <span class="comment"># show errors(0), warnings(1), info(2), hints(3)</span></span><br><span class="line">scv.settings.set_figure_params(<span class="string">'scvelo'</span>) <span class="comment"># for beautified visualization</span></span><br></pre></td></tr></table></figure>
- <h4 id="第二步-读取数据(时间很长)">第二步 读取数据(时间很长)</h4>
- <figure class="highlight python"><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></pre></td><td class="code"><pre><span class="line">loomf = <span class="string">'/home/jovyan/upload/zl_liu/data/data/res/hPB003/velocyto/hPB003.loom'</span></span><br><span class="line">adata = scv.read(loomf, cache=<span class="literal">False</span>)</span><br><span class="line">metadataf = <span class="string">'/home/jovyan/upload/zl_liu/data/data/res/hPB003/velocyto/metadata.csv'</span></span><br><span class="line">meta = pd.read_csv(metadataf, index_col=<span class="number">0</span>)</span><br></pre></td></tr></table></figure>
- <h4 id="第三步-取交集并合并数据">第三步 取交集并合并数据</h4>
- <figure class="highlight python"><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></pre></td><td class="code"><pre><span class="line">tmp = [x <span class="keyword">for</span> x <span class="keyword">in</span> (x[<span class="number">7</span>:<span class="number">23</span>] <span class="keyword">for</span> x <span class="keyword">in</span> adata.obs.index) <span class="keyword">if</span> x <span class="keyword">in</span> meta.index]</span><br><span class="line">meta = meta.loc[tmp]</span><br><span class="line">adata = adata[[<span class="string">f'hPB003:<span class="subst">{x}</span>x'</span> <span class="keyword">for</span> x <span class="keyword">in</span> tmp]]</span><br><span class="line"></span><br><span class="line">test = meta[<span class="string">'cell_type_fig3'</span>]</span><br><span class="line">test.index = adata.obs.index</span><br><span class="line">adata.obs[<span class="string">'cell_type_fig3'</span>] = test</span><br><span class="line"></span><br><span class="line">adata.obsm[<span class="string">'X_pca'</span>] = np.asarray(meta.iloc[:, <span class="number">4</span>:])</span><br><span class="line">adata.obsm[<span class="string">'X_umap'</span>] = np.asarray(meta.iloc[:, <span class="number">2</span>:<span class="number">4</span>])</span><br><span class="line"></span><br><span class="line">sc.pl.pca(adata, color=<span class="string">'cell_type_fig3'</span>)</span><br><span class="line">sc.pl.umap(adata, color=<span class="string">'cell_type_fig3'</span>)</span><br></pre></td></tr></table></figure>
- <h3 id="运行2-计算绘图">运行2: 计算绘图</h3>
- <h4 id="计算">计算</h4>
- <figure class="highlight python"><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></pre></td><td class="code"><pre><span class="line">scv.pp.moments(adata, n_pcs=<span class="number">30</span>, n_neighbors=<span class="number">30</span>)</span><br><span class="line"></span><br><span class="line">scv.tl.recover_dynamics(adata, n_jobs=<span class="number">8</span>)</span><br><span class="line"></span><br><span class="line">scv.tl.velocity(adata, mode=<span class="string">'dynamical'</span>)</span><br><span class="line"></span><br><span class="line">scv.tl.velocity_graph(adata, n_jobs=<span class="number">8</span>)</span><br><span class="line"></span><br><span class="line">adata.write(<span class="string">'hPB003.h5ad'</span>)</span><br></pre></td></tr></table></figure>
- <h4 id="绘图">绘图</h4>
- <figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> matplotlib.pyplot <span class="keyword">import</span> rc_context</span><br><span class="line"><span class="keyword">with</span> rc_context({<span class="string">'figure.figsize'</span>: (<span class="number">12</span>, <span class="number">12</span>)}):</span><br><span class="line"> scv.pl.velocity_embedding_stream(adata, basis=<span class="string">'umap'</span>, color=[<span class="string">'cell_type_fig3'</span>], save = <span class="string">"hPB003 velocity embedding stream.svg"</span>)</span><br></pre></td></tr></table></figure>
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