fpkmToTpm <-function(fpkm) { exp(log(fpkm) -log(sum(fpkm)) +log(1e6)) } countToCPM <-function( counts) { N <- sum(counts) exp(log(counts) +log(1e6) -log(N) ) } expmat %>% mutate( FPKM = countToFpkm(.$count, .$est_len) ) %>%#转FPKMmutate( TPM = countToTpm(.$...
fpkmToTpm<-function(fpkm){exp(log(fpkm)-log(sum(fpkm))+log(1e6))}tpms<-apply(expMatrix,2,fpkmToTpm)#每列的基因 tpms[1:3,]##N1N2N3T1T2T3## 0610005C13Rik0.23204710.17154680.000000.000000.000000.00000## 0610007P14Rik48.390804639.263156046.0400350.0369559.0514067.28521## 0610009B22Rik47.490590758...
CountToTPM <- function(counts, effLen) { rate <- log(counts) - log(effLen) denom <- log(sum(exp(rate))) exp(rate - denom + log(1e6)) } identical(rownames(exp_Count),gle$gene_id) exprSetTPM <- apply(exp_Count, 2, CountToTPM, effLen = gle$length) 参考文章: 1、生物信息...
countDf$effLength <- countDf$length - 203.7 + 1 countDf$tpm <- with(countDf, countToTpm(count, effLength)) countDf$fpkm <- with(countDf, countToFpkm(count, effLength)) with(countDf, all.equal(tpm, fpkmToTpm(fpkm))) countDf$effCounts <- with(countDf, countToEffCounts(count, le...
tpm:counts先对基因长度标准化,再对测序文库标准化; cpm:counts只对测序文库标准化。 测序文库相对容易计算,直接使用colSums()函数即可;而基因长度则比较难求,首先要了解基因长度有不同的定义标准,其次要知道哪些R包提供相关生物数据。我目前了解到了以下三种方法,以及根据与官方fpkm验证,最终选择第三种方法用于后续的分...
countToTpm <- function(counts, effLen) { rate <- log(counts) - log(effLen) denom <- log(sum(exp(rate))) exp(rate - denom + log(1e6)) } countToFpkm <- function(counts, effLen) { N <- sum(counts) exp( log(counts) + log(1e9) - log(effLen) - log(N) ) } fpkmToTp...
(fpkm))+log(1e6))}countToCPM<-function(counts){N<-sum(counts)exp(log(counts)+log(1e6)-log(N))}expmat%>%mutate(FPKM=countToFpkm(.$count,.$est_len))%>%#转FPKMmutate(TPM=countToTpm(.$count,.$est_len))%>%#转TPMmutate(CPM=countToCPM(.$count))%>%#转CPMselect(-est_len)%>...
edgeR::cpm(counts) 二、由Counts计算FPKM/RPKM和TPM 有许多文章已经给出了这几种计数方式的计算和转化关系,如What the FPKM? A review of RNA-Seq expression units | The farrago (wordpress.com)。 countToTpm <- function(counts, effLen) { rate <- log(counts) - log(effLen) denom <- log(sum...
1importpandas as pd2importnumpy as np345defread_counts2tpm(df, sample_name):6"""7convert read counts to TPM (transcripts per million)8:param df: a dataFrame contains the result coming from featureCounts9:param sample_name: a list, all sample names, same as the result of featureCounts10:...
FPKM = \frac{{\text{{count}}}{{\text{{length}} / 1000}} \times \frac{10^9}{\text{{total counts}}} ] 其中,length是基因的长度,count是读取的计数。 # 计算FPKM值的函数calculate_fpkm<-function(data){# 计算每个样本的总计数total_counts<-colSums(data[,-(1:2)])# 排除基因ID和长度列#...