如今的测序和八年前的芯片差异大吗 / 开普饭

课程配套思维导图见：https://mubu.com/doc/7A3T8hpUlLv
miRNA相关资料在：https://share.weiyun.com/k6ZbUg6H

但是阅读量超级低哦，可能是因为做miRNA-Seq数据的人并不多吧，实际上miRNA-Seq数据的绝大部分的分析经验都是可以从mRNA迁移过来，包括测序和芯片。为了调动我视频课程的收听率，刻意寻找了一个同样的实验设计但是使用了测序和芯片两个不同技术手段来量化miRNA表达量的数据集给大家做练习题：

miRNA测序是 Illumina HiSeq 2000 (Homo sapiens)

实验设计很简单：miRNA and mRNA profiles in peripheral blood mononuclear lymphocytes (PBMC) from 5 biopsy proven IgAN patients and 4 healthy controls were determined by next-generation sequencing and gene expression array. The differentially expressed miRNA and mRNA were conbined analyzed later.

链接：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE125998

GSM3587520 PBMC_IgAN1 GSM3587521 PBMC_IgAN2 GSM3587522 PBMC_IgAN3 GSM3587523 PBMC_IgAN4 GSM3587524 PBMC_IgAN5 GSM3587525 PBMC_HC1 GSM3587526 PBMC_HC2 GSM3587527 PBMC_HC3 GSM3587528 PBMC_HC4

提供了分析好的表达矩阵：ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE125nnn/GSE125998/suppl/GSE125998_mir21_processed_data.xlsx 下载这个文件即可走差异分析策略啦，如果你实在是感兴趣miRNA-seq数据分析，也可以看我B站免费视频教学课程，miRNA-Seq数据挖掘实战

教学视频免费在B站：https://www.bilibili.com/video/BV1zK411n7qr
课程配套思维导图见：https://mubu.com/doc/7A3T8hpUlLv
miRNA相关资料在：https://share.weiyun.com/k6ZbUg6H

miRNA芯片是Agilent-019118 Human miRNA Microarray 2.0

实验设计也很简单：To identify miRNAs differentially expressed in IgAN respect to healthy subjects (HS), we analyzed the global miRNA expression profile in PBMCs from IgAN patients and HS using the miRNA microarray approach. Among 723 human miRNAs represented on the microarrays, 147 were expressed in each sample.

分析结果是：Applying a fold change threshold > 2 (false discovery rate < 0.01), 35 miRNAs were found to be significantly up-regulated and 2 were significantly down-regulated in IgAN. Complete list of differentially expressed miRNAs is shown in Table S1.

链接：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE25590

GSM627751 RNA isolated from PBMCs (IgAN_1) GSM627779 RNA isolated from PBMCs (IgAN_2) GSM627781 RNA isolated from PBMCs (IgAN_3) GSM627926 RNA isolated from PBMCs (IgAN_4) GSM627964 RNA isolated from PBMCs (IgAN_5) GSM627983 RNA isolated from PBMCs (IgAN_6) GSM627984 RNA isolated from PBMCs (IgAN_7) GSM627998 RNA isolated from PBMCs (HS_1) GSM627999 RNA isolated from PBMCs (HS_2) GSM628000 RNA isolated from PBMCs (HS_3) GSM628001 RNA isolated from PBMCs (HS_4) GSM628002 RNA isolated from PBMCs (HS_5) GSM628003 RNA isolated from PBMCs (HS_6) GSM628004 RNA isolated from PBMCs (HS_7)

学徒作业

完成上面的两个数据集的标准差异分析，做两个图：

第一个图是韦恩图，看各自数据集的上下调基因集的交集
第二个图是logFC的散点图，并且附上回归方程，相关性系数

而差异分析呢，可以看到我五年前的教程，推文在：

反正这些芯片技术都是十几年前的了，大家不要觉得我五年前的教程有什么过时的地方哈。

或者跟着下面的课程《GEO数据挖掘课程》即可：

《GEO数据挖掘课程》

我把3年前的收费视频课程：3年前的GEO数据挖掘课程你可以听3小时或者3天甚至3个月，免费到B站:

这个课程超级棒，B站免费学习咯：https://m.bilibili.com/video/BV1dy4y1C7jz
配套代码在GitHub哈：https://github.com/jmzeng1314/GSE76275-TNBC
TCGA数据库挖掘，代码在：https://github.com/jmzeng1314/TCGA_BRCA
GTEx数据库挖掘，代码在：https://github.com/jmzeng1314/gtex_BRCA
METABRIC数据库挖掘，代码在：https://github.com/jmzeng1314/METABRIC

然后马上就有了3千多学习量，而且有学员给出来了图文并茂版本万字笔记，让我非常感动！

扫描下面二维码马上就可以学习起来啦，笔记需要至少半个小时来阅读哦！

有一个练习题：《GEO数据挖掘课程》配套练习题，关于这个课程学徒也写了一系列笔记：学徒写的《GEO数据挖掘课程》的配套笔记完结撒花

如今的测序和八年前的芯片差异大吗

miRNA测序是 Illumina HiSeq 2000 (Homo sapiens)

miRNA芯片是Agilent-019118 Human miRNA Microarray 2.0

学徒作业

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