以“TPM”与“FPKM”为关键词,仅找到了两篇匹配度比较高的文章,一篇题为"TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository"很好地展现了这三个常用的“表达量”在表现组内的一致性与组间的...
Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols. RNA. 2020 Aug;26(8):903-909. Zhao, Y., Li, MC., Konaté, M.M. et al. TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the...
RPKM/FPKM does not represent the accurate measure of relative RNA molar concentration (rmc) and can be biased towards identifying the differentially expressed genes as the total normalized counts for each sample will be different 3,4. TPM is proposed as an alternative to the RPKM. RPKM or FPKM...
With RPKM or FPKM, the sum of normalized reads in each sample can be different. Thus, if the RPKM for gene A in Sample 1 is 3.33 and the RPKM in Sample 2 is 3.33, I would not know if the same proportion of reads in Sample 1 mapped to gene A as in Sample 2. This is because ...
以下命令是normalizeGeneCounts作者的说明文件中的命令 # normalizeGeneCounts## DescriptionFunctiontakes raw counts ofNGSdata and normalize to[CPM,RPKMor TPM](https://www.rna-seqblog.com/rpkm-fpkm-and-tpm-clearly-explained/).## UsagenormalizeGeneCounts(counts,TxDb,method)## Arguments*counts*Adata fr...
有了基因长度,下面的计算就比较简单了,据FPKM的公式定义一个函数然后调用(选择非冗余外显子) CountToFPKM <- function(counts, effLen) { N <- sum(counts) exp( log(counts) + log(1e9) - log(effLen) - log(N) ) } identical(rownames(exp_Count),gle$gene_id) exprSetFPKM <- apply(exp_Cou...
Zhao, Y., Li, MC., Konaté, M.M. et al. TPM, FPKM, or Normalized Counts? A Comparative ...
Zhao, Y., Li, MC., Konaté, M.M. et al. TPM, FPKM, or Normalized Counts? A Comparative ...