6257rv7 发表于 2024-6-14 14:07:44

癌症基因表达数据库 (一)


    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">癌症<span style="color: black;">科研</span><span style="color: black;">始终</span>是生物医学<span style="color: black;">行业</span>的热点。<span style="color: black;">尤其</span>是随着高通量基因测序技术的<span style="color: black;">显现</span>,癌症<span style="color: black;">关联</span>的生物数据呈现着指数式增长。这类数据<span style="color: black;">繁杂</span>而多样,<span style="color: black;">包括</span>了基因组变异、基因表达、甲基化数据等。<span style="color: black;">因此呢</span>,为了使<span style="color: black;">更加多</span>的<span style="color: black;">研究</span>人员能够方便<span style="color: black;">有效</span>地<span style="color: black;">运用</span>这些数据,越来越多的数据库与网页服务器<span style="color: black;">工具</span>被设计。本期<span style="color: black;">博主</span>就先和<span style="color: black;">大众</span><span style="color: black;">一块</span>学习与癌症基因表达<span style="color: black;">关联</span>的数据库吧(表<strong style="color: blue;">1.1</strong>)。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">表1.1.</strong> 癌症基因表达数据库</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q3.itc.cn/images01/20240410/7691682908324925b53bbd625dfed38a.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">TCGA(https://cancergenome.nih.gov/)与ICGC(https://dcc.icgc.org/)都是综合型数据库。它们的数据都是<span style="color: black;">源自</span>于<span style="color: black;">有些</span>大规模癌症合作项目,数据信息最为丰富。然而<span style="color: black;">无</span><span style="color: black;">供给</span>交互式的分析服务,相当于一级数据库。<span style="color: black;">因此呢</span>,这两个数据库只<span style="color: black;">供给</span>了基因表达数据(FPKM归一化<span style="color: black;">或</span>readscounts数据)的下载服务(图<strong style="color: blue;">1.1</strong>,图<strong style="color: blue;">1.2</strong>)。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q7.itc.cn/images01/20240410/2ca779742b6342b183a0c4323e018302.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.1.</strong> TCGA RNA-seq数据</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q3.itc.cn/images01/20240410/66952797f37f49e3ab6c92a7b3f82707.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">添加<span style="color: black;">照片</span>注释,不超过 140 字(可选)</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.2.</strong> ICGC中数据下载页面</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">CGWB(https://cgwb.nci.nih.gov/)<span style="color: black;">实质</span>上是一个癌症数据可视化的数据库。其基因表达数据<span style="color: black;">重点</span>来自于TCGA。对这部分数据展示,CGWB<span style="color: black;">供给</span>了两种方式:1.以柱状图形式呈现每一个癌症样本中基因的表达水平分布(图<strong style="color: blue;">1.3</strong>);2.以热图形式将该数据与其它数据(如拷贝数变异数据、临床数据)进行了整体展示。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q0.itc.cn/images01/20240410/f8f473e83d304900a6d7712b8adc7cf7.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.3.</strong> TCGABLCA(Bladderurothelial carcinoma)病人的基因表达分布</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">cBioPortal(http://www.cbioportal.org/)是一个综合性癌症数据分析数据库,<span style="color: black;">供给</span>了数据<span style="color: black;">查找</span>、展示、分析以及下载等功能。<span style="color: black;">日前</span>,该数据库收录了体细胞突变、DNA拷贝数变异、基因表达、DNA甲基化、蛋白质丰度和临床等数据。这些数据<span style="color: black;">重点</span>来自于TCGA、CCEL(CancerCell Line Encyclopedia)和<span style="color: black;">有些</span>癌症<span style="color: black;">科研</span>工作。<span style="color: black;">咱们</span><span style="color: black;">能够</span><span style="color: black;">经过</span>四步来进行数据的<span style="color: black;">查找</span>(如图<strong style="color: blue;">1.4</strong>)。<span style="color: black;">针对</span>基因表达数据的分析<span style="color: black;">重点</span><span style="color: black;">包含</span>了热图整体性展示(图<strong style="color: blue;">1.5</strong>)、与其它数据(如拷贝数变化、DNA甲基化以及蛋白质水平)的<span style="color: black;">相关</span>分析(图<strong style="color: blue;">1.6</strong>)、依据临床信息划分的样本集之间的表达比较分析(图<strong style="color: blue;">1.6</strong>)、基因间表达<span style="color: black;">关联</span>性分析(图<strong style="color: blue;">1.7</strong>)。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q0.itc.cn/images01/20240410/05224ecb8cdc4cdf8584977bc7e10fe7.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.4.</strong>cBioPortal<span style="color: black;">查找</span>页面</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q3.itc.cn/images01/20240410/a593faa077ac48aba412d651faa877e8.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.5.</strong>基因表达热图</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q3.itc.cn/images01/20240410/add6ca78dec948b3b5e20126e7ae6349.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.6.</strong> cBioPortal Plots界面</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q8.itc.cn/images01/20240410/d3f6f023b2624550b444433f52e72d6d.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.7.</strong> cBioPortalco-expression界面</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">GEPIA(http://gepia.cancer-pku.cn/index.html)是一个基因表达数据交互式分析的数据库,表达数据<span style="color: black;">重点</span>来自TCGA和GTEx(https://www.gtexportal.org/home/)。<span style="color: black;">日前</span>收录了9736个癌症组织样本(33种癌症)和8587正常组织样本的表达数据。该数据库功能<span style="color: black;">非常</span>强大,<span style="color: black;">供给</span>了差异表达分析、动态展示、基于基因表达的<span style="color: black;">存活</span>分析、表达<span style="color: black;">类似</span>基因分析、基因表达<span style="color: black;">关联</span>性以及主<span style="color: black;">成份</span>分析。并<span style="color: black;">供给</span>了非常丰富结果展示(图<strong style="color: blue;">1.8</strong>)。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q9.itc.cn/images01/20240410/5aae40cb8f264a57869db171e7a442ce.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">添加<span style="color: black;">照片</span>注释,不超过 140 字(可选)</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.8.</strong> GEPIA分析的结果展示</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">CRN(http://syslab4.nchu.edu.tw/)数据库<span style="color: black;">亦</span>是一个基因表达数据分析数据库。其表达数据<span style="color: black;">重点</span><span style="color: black;">源自</span>于GEO(https://www.ncbi.nlm.nih.gov/geo/)与TCGA。<span style="color: black;">日前</span>收录了28种癌症共11447个样本的表达数据,并<span style="color: black;">按照</span>样本的临床信息将每种癌症分<span style="color: black;">成为了</span>若干个子数据集。该数据库<span style="color: black;">运用</span>简单直接。<span style="color: black;">咱们</span>只需<span style="color: black;">选取</span>了癌症类型和配对子集,就<span style="color: black;">能够</span>进行差异表达分析与mRNA-lncRNA共表达网络构建(图<strong style="color: blue;">1.9</strong>)。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q5.itc.cn/images01/20240410/3d1f8536dc3a4d88b6486063538f7bb4.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">添加<span style="color: black;">照片</span>注释,不超过 140 字(可选)</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.9.</strong> CRN数据库</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">tRF2Cancer(http://rna.sysu.edu.cn/tRFfinder/)是一个网页服务型数据库。<span style="color: black;">供给</span>了基于小RNA深度测序数据的tRFs(tRNA-derived small RNA Fragments)鉴定<span style="color: black;">工具</span>-tRFfinder;估计癌症样本中tRFs表达丰度<span style="color: black;">工具</span>-tRFinCancer以及基因组展示tRFs的<span style="color: black;">工具</span>-tRFBrowser<strong style="color: blue;">。</strong><span style="color: black;">日前</span>,该数据库共鉴定了TCGA中32种癌症共10991个样本的tRFs。<span style="color: black;">咱们</span>只需输入fasta格式的小RNA序列(图<strong style="color: blue;">1.10</strong>),就<span style="color: black;">能够</span>得到预测的tRFs序列<span style="color: black;">关联</span>信息。<span style="color: black;">包含</span>序列、结构、表达丰度、基因组位置等信息(图<strong style="color: blue;">1.11</strong>)。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q8.itc.cn/images01/20240410/4a8f7911429e413b9d9a4139384f8267.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.10.</strong> tRFfinder 提交页面</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q9.itc.cn/images01/20240410/2bd97d533deb443896e23593136d2bf7.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.11.</strong> tRF2Cancer<span style="color: black;">查找</span>结果</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">dbDEMC 2.0 (http://www.picb.ac.cn/dbDEMC/)是一个存储和展示癌症样本中差异表达miRNA的数据库。<span style="color: black;">日前</span>,该数据库收录了36种癌症共2224个差异表达miRNA。这些基因是基于GEO和TCGA中209套数据集分析得到的。<span style="color: black;">咱们</span><span style="color: black;">能够</span>基于基因信息<span style="color: black;">或</span><span style="color: black;">科研</span>实验(experiments)来<span style="color: black;">查找</span>miRNA结果。如图<strong style="color: blue;">1.12</strong>中A和C,点击差异基因列表中miRNA ID<span style="color: black;">能够</span>得到这个基因的<span style="color: black;">仔细</span>信息(E)。<span style="color: black;">另外</span>,该数据库还<span style="color: black;">能够</span><span style="color: black;">经过</span><span style="color: black;">选取</span>多个癌症,用热图的形式展示了miRNA的差异表达信息(图<strong style="color: blue;">1.13</strong>)。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q2.itc.cn/images01/20240410/2a09b3b5cabc46d784337e0504276bc4.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.12.</strong> dbDEMC 2.0数据库</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q8.itc.cn/images01/20240410/2370fcf80ee348c590835f8686fcf61c.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.13.</strong> dbDEMC 2.0数据库的Meta-profiling Heatmap分析</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">ISOexpresso(http://wiki.tgilab.org/ISOexpresso/)是一个<span style="color: black;">供给</span>癌症样本中转录本表达信息和分析的数据库。该数据库<span style="color: black;">日前</span>收录了TCGA中30中癌症类型共10422样本的基因和转录本表达信息。<span style="color: black;">咱们</span><span style="color: black;">能够</span><span style="color: black;">经过</span><span style="color: black;">选取</span>不同组织、癌症类型和基因名进行搜索(图1.14<strong style="color: blue;">a</strong>)。<span style="color: black;">查找</span>结果<span style="color: black;">包括</span>了该基因转录本的注释信息以及不同转录本之间的表达<span style="color: black;">状况</span>(图1.14 <strong style="color: blue;">b</strong>)。<span style="color: black;">倘若</span><span style="color: black;">咱们</span><span style="color: black;">同期</span><span style="color: black;">选取</span>了癌症和正常样本(Normal-tumor comaprison选项),数据库还会给出转录本肿瘤特异性信息(图<strong style="color: blue;">1.15</strong>)。<span style="color: black;">另一</span>,我们还<span style="color: black;">能够</span>上传癌症突变数据,该数据库会基于该癌症中转录本表达信息,对突变数据进行注释。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q8.itc.cn/images01/20240410/b73ea87ee45b436e8c52fe6ac1bf14e7.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.14.</strong> ISOexpresso数据库<span style="color: black;">查找</span>和结果呈现</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q4.itc.cn/images01/20240410/a030460d3c2b49ef95b1b84f6db3e43d.jpeg" style="width: 50%; margin-bottom: 20px;"></p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">添加<span style="color: black;">照片</span>注释,不超过 140 字(可选)</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">图1.15.</strong> 癌症组织特异性信息</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">以上<span style="color: black;">便是</span>这期的<span style="color: black;">所有</span>内容啦,<span style="color: black;">博主</span>相信这些数据库<span style="color: black;">必定</span>会给<span style="color: black;">咱们</span>带来意想不到的方便。还有,<span style="color: black;">这儿</span>介绍的是RNA-seq数据的癌症数据库哦,还有<span style="color: black;">非常多</span>基于基因芯片数据的癌症数据库。那就下期再会了。</p>
    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">参考文献</strong></p>
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    <p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">2. International Cancer Genome C, Hudson TJ,Anderson W, Artez A, Barker AD, Bell C, Bernabe RR, Bhan MK, Calvo F, Eerola Iet al: International network of cancer genome projects. Nature 2010,464(7291):993-998.</p>
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vip51888 发表于 2024-9-7 15:20:07

对于这个问题,我有不同的看法...
页: [1]
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