library(DESeq2) colData <- data.frame( group = c("Sample1_FPKM", "Sample2_FPKM", "Sample3_FPKM", "Sample4_FPKM","Sample5_FPKM","Sample6_FPKM"), condition = c("fpkm", "fpkm", "fpkm", "fpkm","fpkm","fpkm")) dds <- DESeqDataSet(counts=ABC_1,colData=colData,design=~group)Error in DESeqDataSet(counts = ABC_1, colData = colData, design = ~group) : unused arguments (counts = ABC_1, colData = colData)
时间: 2023-07-21 18:06:51 浏览: 192
AltAnalyze-2.1.0.8-py2.py3-none-any.whl.zip
根据你提供的代码和错误信息,看起来你在调用DESeqDataSet函数时遇到了问题。
DESeqDataSet函数不接受直接传递counts和colData参数。相反,你需要先创建一个countData对象,然后将其与colData一起传递给DESeqDataSetFromMatrix函数。
请尝试以下代码:
```R
library(DESeq2)
# 创建countData对象
countData <- ABC_1 # 假设ABC_1是你的浮点数型的countData
# 创建colData对象
colData <- data.frame(
group = c("Sample1_FPKM", "Sample2_FPKM", "Sample3_FPKM", "Sample4_FPKM","Sample5_FPKM","Sample6_FPKM"),
condition = c("fpkm", "fpkm", "fpkm", "fpkm","fpkm","fpkm")
)
# 创建DESeqDataSet对象
dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~ group)
# 进行差异表达分析
dds <- DESeq(dds)
```
这样,你应该能够成功创建DESeqDataSet对象并进行差异表达分析。
如果仍然遇到问题,请提供更多的代码和错误信息,以便我可以更好地帮助你。
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