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  • RNAseq biological replicates not clustering in PCA plots
    I am currently trying to do the differential expression analysis with DESeq2 but the biological replicates will not cluster together when I make the PCA plot or correlation heatmap
  • RNA-seq转录组数据分析？ - 知乎
    · DESeq2：在运行DESeq ()函数时，它会自动独立于假设检验，预先过滤掉低表达基因。 其默认标准是：所有样本中归一化counts的平均值小于10的基因会被自动过滤掉。 用户通常不需要手动额外过滤，除非有特殊原因。
  • The confusion of using TPM (transcripts per million)
    The latter is convenient, and sometimes per-million might be good enough for visualization I never do it though, I always use normalized (or vst) counts from DESeq2 or edgeR For differential analysis of bulk data one commonly uses raw counts which are then normalized internally by the established frameworks such as DESeq2, edgeR or
  • TCGA系列6-DeSeq2,edgeR,limma差异分析 - 知乎
    TCGA系列6-DeSeq2,edgeR,limma差异分析,差异分析的R语言工具库有很多，主流工具为DeSeq2,edgeR,limma，我们这次同时使用上述三个包进行差异基因分析，教生信新手跑通流程并且拿到差异分析结果
  • Would DESeq2 be appropriate or should I use another tool for differential gene expression?
    We want to compare the gene expression (Or rather abundance of RNA) between samples based on the Day subgroup Since the same sample culture batch has not been sequenced with replicates, and there is variance in number of samples per group, I was wondering if DESeq2 would be a valid option, as the documentation does mention that without replicates, the output from DESeq2 should be considered
  • DeSeq2筛选差异基因出现以下错误，要怎么解决？
    DESeq2包主要提供了三种标准化处理方法： normalized_counts：就是DESeq2差异分析采用的标准化方式——比值中位数法（median of ratios）； variance stabilizing transformation (vst)：vst通过非线性转换来平衡数据中的高变异和低变异，减少低计数值样本的变异，使得表达量的分布更加接近正态分布。适用于样本量
  • r - Ranking metric in GSEA - Bioinformatics Stack Exchange
    My question is whether it is acceptable to use the Wald statistic from DeSeq2 to rank the gene list? I have seen in the GSEA application that the signal to noise ratio is used but is the Wald statistic sufficient? If not then is there an easyish way to calculate the signal to noise ratio in R given a normalised count matrix? Thanks
  • RNA-seq 如何进行转录组数据分析？ - 知乎
    在这里我们使用R中 DESeq2 包来进行差异表达分析，用到的输入文件为上一篇生成的表达矩阵（gene_count csv）文件。 差异表达分析可以使用Linux上的R，也可以使用RStudio来进行分析。 RStudio有Windows版本，绘图可以实时显示，方便调整参数。
  • Is it possible to do DEG analysis without replicates?
    And I noticed that DEG analysis tools such as DESeq2 edgeR etc cannot be applied for data with no replicates So, I just drew a heatmap with expression value (TPM) of genes of interest, using NMF (aheatmap) But now I want to perform DEG analysis across the three samples Is there anything I can try for the analysis?
  • RStudio怎么下DESeq2包？ - 知乎
    找了一下代码，然后不会了，在线等，谢谢！





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