之前分析遇到2个问题： 1.样本只有一个，没有replicates，是不是就没有办法进行分析？ 2.一个样本有3个重复，另外一个只有1个，怎么进行分析？

http://www.biotrainee.com/thread-752-1-1.html 参考文献是这篇-gfold https://pubmed.ncbi.nlm.nih.gov/22923299/

Example 3: Identify differentially expressed genes without replicates

Example 4: Identify differentially expressed genes with replicates

Example 5: Identify differentially expressed genes with replicates only in one condition

Only the first group contains replicates. In this case, the variance estimated based on the first group will be used as the variance of the second group

All fields in a output file are separated by TABs.

The output file contains 5 columns ：共有5列，顺序如下

1.GeneSymbol

2.GeneName

3.Read Count

4.Gene exon length

5.RPKM

生成文件：

1 GeneSymbol

2 GeneName

3 GFOLD: GFOLD value for every gene. The GFOLD value could be considered as a reliable log2 fold change. It is positive/negative if the gene is up/down regulated. The main usefulness of GFOLD is to provide a biological meanlingful ranking of the genes. The GFOLD value is zero if the gene doesn't show differential expression. If the log2 fold change is treated as a random variable, a positive GFOLD value x means that the probability of the log2 fold change (2nd/1st) being larger than x is (1 - the paramete specified by -sc); A negative GFOLD value the parameter specified by -sc). If this file is sorted by this column in descending order then genes ranked at the top are differentially up-regulated and genes ranked at the bottom are differentially down-regulated. Note that a gene with GFOLD value 0 should never be considered differentially expressed. However, it doesn't mean that all genes with non-negative GFOLD value are differentially expressed. For taking top differentially expressed genes, the user is responsible for selecting the cutoff. 4 E-FDR: Empirical FDR based on replicates. It is always 1 when no replicates are available

5 log2fdc: log2 fold change. If no replicate is available, and -acc is T, log2 fold change is based on read counts and normalization constants. Otherwise, log2 fold change is based on the sampled expression level from the posterior distribution.

6： 1stRPKM: The RPKM for the first condition. It is available only if gene length is available. If multiple replicates are available, the RPKM is calculated simply by summing over replicates.Because RPKM is acturally using sequencing depth as the normalization constant, log2 fold change based on RPKM could be different from the log2fdc field.

7：2ndRPKM: The RPKM for the second condition. It is available only if gene length is available. Please refer to 1stRPKM for more information.