From data in the long format to data in the wide formatFrancesco BartolucciSilvia PandolfiUniversity of Perugia (IT)
R语言使用data.table包将dataframe宽表转化为长表(wide format to long format)、使用id.vars参数指定不变的列名称列表、使用variable.name指定原多个数据列名称生成的新数据列名称 library(data.table) long <- melt(setDT(wide), id.vars = c("Code","Country"), variable.name = "year") #其他方案...
olddata_wide#> subject sex control cond1 cond2#> 1 1 M 7.9 12.3 10.7#> 2 2 F 6.3 10.6 11.1#> 3 3 F 9.5 13.1 13.8#> 4 4 M 11.5 13.4 12.9library(tidyr)# The arguments to gather():# - data: Data object# - key: Name of new key column (made from names of data columns)#...
data_long3<-data_wide%>%# Apply gather functiongather(variable,value,-c(ID1, ID2))data_long3# Print long data# ID1 ID2 variable value# 1 A b x 1# 2 A c x 2# 3 B c x 3# 4 C a x 4# 5 B d x 5# 6 A b y 6# 7 A c y 7# 8 B c y 8# 9 C a y 9# 10...
readLength, sex into indicators (Note: this is required by most regression programs likePEERor Matrix-eQTL, since for example the batch 5 does not match it's higher than batch 1, unlike the age or PMI). So, we need to convert this long format into wide format. Here is my R code fo...
This is to continue on the topic of using the melt/cast functions in reshape to convert between long and wide format of data frame. Here is the example I found helpful in generating covariate table required for PEER (or Matrix_eQTL) analysis:Here ...
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1e). These data suggest that both a bioactive lipid(s) and metabolite(s) may function as cell non-autonomous UPR-inducing secreted signals. Lipotoxicity-induced UPR-activating long-chain ceramide secretion from myotubes To identify the cell non-autonomous UPR-inducing lipid species we performed ...
We evaluate QServe W4A8KV4 quantization on a wide range of mainstream LLMs. QServe consistently outperforms existing W4A4 or W4A8 solutions from the accuracy perspective, while providing State-of-the-Art LLM serving efficiency. When serving the large language models Llama-3-8B and Qwen1.5-72B ...
Our analysis pipeline was adjusted to enable analysis of experimental data. The first temporal derivative was sufficient to remove non-stationarity effects in ECM remodeling fluctuations of single and pairs of communicating fibroblast cells (Fig. S5), so we could avoid the second derivative in the ...