小编nik*_*nik的帖子

自昨晚以来我一直忙于这个问题,我无法弄清楚如何去做.

我想要做的是将df1字符串与df2字符串匹配并获得类似的字符串

我做的就像这样

# a function to arrange the data to have IDs for each string 
    normalize <- function(x, delim) {
      x <- gsub(")", "", x, fixed=TRUE)
      x <- gsub("(", "", x, fixed=TRUE)
      idx <- rep(seq_len(length(x)), times=nchar(gsub(sprintf("[^%s]",delim), "", as.character(x)))+1)
      names <- unlist(strsplit(as.character(x), delim))
      return(setNames(idx, names))
    }

# a function to arrange the second df  
lookup <- normalize(df2[,1], ",")

# a function to match them and give the IDs
process <- function(s) {
  lookup_try <- lookup[names(s)]
  found <- which(!is.na(lookup_try))
  pos <- …

实际上我试图绘制一个图,但它放置并显示彼此的所有列(线),因此它不具有代表性.我尝试制作模拟数据并向您展示我如何绘制它,并向您展示我想要的内容

我不知道如何制作如下所示的示例数据,但这里是我做的

set.seed(1)
M <- matrix(rnorm(20),20,5)
x <- as.matrix(sort(runif(20, 5.0, 7.5)))
df <- as.data.frame(cbind(x,M))

在创建数据框之后,我将通过熔化并使用ggplot来绘制所有列与第一个列的关系

require(ggplot2)
require(reshape)
dff <- melt(df ,  id.vars = 'V1')
b <- ggplot(dff, aes(V1,value)) + geom_line(aes(colour = variable))

我想在每一行之间有特定的距离(在这种情况下我们有6),如下所示.在一个维度,它是V1,在另一个维度,它是列的数量.我不关心功能,我只想要照片

我正在尝试从NCBI网站获取FASTA文件，我使用以下功能

getncbiseq <- function(accession){
  dbs <- c()
  for (i in 1:numdbs){
    db <- dbs[i]
    choosebank(db)
    resquery <- try(query(".tmpquery", paste("AC=", accession)),silent = TRUE)
    if (!(inherits(resquery, "try-error"))){
      queryname <- "query2"
      thequery <- paste("AC=",accession,sep="")
      query(`queryname`,`thequery`)
      # see if a sequence was retrieved:
      seq <- getSequence(query2$req[[1]])
      closebank()
      return(seq)
    }
    closebank()
  }
  print(paste("ERROR: accession",accession,"was not found"))
}    

当我尝试检索序列时

mydata <- getncbiseq("NC_001477")

getSequence（query2 $ req [[1]]）中的错误：找不到对象'query2'

还有缩短这些循环功能的更好方法吗？

如果我用

query('queryname','the query')
#or 
query("queryname","thequery")

我收到另一个错误

query（“ queryname”，“ thequery”）中的错误：无效的请求：“（^）处的未知列表：\”（^）thequery \“”

我试图在尽可能多的列和组合中找到相同的字符串。例如，我有这样的数据

df<-structure(list(first = c("SNTM1", "STTTT2", "STOLA", "STOMQ", 
"STR2", "SUPTY1", "TBNHSG", "TEYAH", "TMEIL1", "TMEIL2", "TMEIL3", 
"TNIL", "TREUK", "TTRK", "TRRFK", "UBA52", "YIPF1", NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA), second = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, "SNTLK", "STTTFSG", "STOIU", "STOMQ", "STR25", 
"SUPYHGS", "TBHYDG", "TEHDYG", "TMEIL1", "YIPF1", NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA), second2 …

如果你能告诉我如何将代码从Java翻译成python,我会很高兴.
一个人应该手动吗？有没有自动转换它的工具？

这是我的数据

df<- structure(list(name = structure(c(2L, 12L, 1L, 16L, 14L, 10L, 
9L, 5L, 15L, 4L, 8L, 13L, 7L, 6L, 3L, 11L), .Label = c("All", 
"Bab", "boro", "bra", "charli", "delta", "few", "hora", "Howe", 
"ist", "kind", "Kiss", "myr", "No", "TT", "where"), class = "factor"), 
    value = c(1.251, -1.018, -1.074, -1.137, 1.018, 1.293, 1.022, 
    -1.008, 1.022, 1.252, -1.005, 1.694, -1.068, 1.396, 1.646, 
    1.016)), .Names = c("name", "value"), class = "data.frame", row.names = c(NA, 
-16L))

这是我所做的

d <- dist(as.matrix(df$value),method = "euclidean")
#compute cluster membership
hcn …

我正在尝试减小 heatmap.2 颜色键的大小

现在是这样的

key=T,  # add the key color
key.title =NA,
cexRow = 0.75, 
cexCol=0.75,

我想降低它的高度并变成这样

这就是我绘制热图的方式

heatmap.2(mat_data,
          key=T,  # add the key color
          key.xlab="label",
          key.title =NA,
          cexRow = 0.75, 
          cexCol=0.75,
          #lhei = c(5,5),
          #cellnote = mat_data,  # will display the values 
          main = "title to be shonwn ", # heat map title
          #notecol=NA,          # change font color of cell labels to black
          density.info="none",  # turns off density plot inside color legend
          trace="none",         # turns off trace lines inside …

我有这样的数据

data<- structure(list(sample = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", 
"B"), class = "factor"), y = c(0.99999652, 0.99626012, 0.94070452, 
0.37332406, 0.57810894, 0.37673758, 0.22784684, 0.35358141, 0.21253558, 
0.17715703, 0.99999652, 0.86403956, 0.64054516, 0.18448824, 0.40362691, 
0.10791682, 0.06985696, 0.07384465, 0.0433271, 0.02875159), time = c(100L, 
150L, 170L, 180L, 190L, 220L, 260L, 270L, 300L, 375L, 100L, 150L, 
170L, 180L, 190L, 220L, 260L, 270L, 300L, 375L), x = c(0.9999965, 
0.9981008, 0.9940164, …

我问了一个不太清楚的问题.所以我试着以一种可以理解的方式解释它.这是我的数据

我的数据看起来像这样

看起来像这样

#             V1      V2               V3
#1                 Q9UNZ5             Q9Y2W1
#2 Q9ULV4;Q6QEF8                     
#3                                    Q9UNZ5
#4                  Q9H6F5              
#5                  Q9H2K0     Q9ULV4;Q6QEF8
#6                  Q9GZZ1            Q9UKD2
#7        Q9H6F5    Q9GZZ1            Q9GZZ1
#8        Q9GZZ1                      Q9NYF8
#9        Q9BWS9                     

我想删除所有这些中的重复字符串,例如,V1我们第一次拥有所有字符串,所以我们不删除任何东西只是安排他们有

Q9ULV4
Q6QEF8
Q9H6F5
Q9GZZ1 
Q9BWS9

然后我们用第一列检查第二列字符串,然后删除那些重复的列并再次排列它们.对于第三列,我们检查第一列和第二列的字符串,如果相似,则我们删除然后排列它们.所以输出应该如下所示.

Q9ULV4  Q9UNZ5  Q9Y2W1
Q6QEF8  Q9H2K0  Q9UKD2
Q9H6F5          Q9NYF8
Q9GZZ1          
Q9BWS9          

它与我提出的任何问题都不相似; 所以,如果仍然不清楚,请评论,我试着解释一下

这是我的数据

df<- structure(list(name = structure(c(2L, 12L, 1L, 16L, 14L, 10L, 
9L, 5L, 15L, 4L, 8L, 13L, 7L, 6L, 3L, 11L), .Label = c("All", 
"Bab", "boro", "bra", "charli", "delta", "few", "hora", "Howe", 
"ist", "kind", "Kiss", "myr", "No", "TT", "where"), class = "factor"), 
    value = c(1.251, -1.018, -1.074, -1.137, 1.018, 1.293, 1.022, 
    -1.008, 1.022, 1.252, -1.005, 1.694, -1.068, 1.396, 1.646, 
    1.016)), .Names = c("name", "value"), class = "data.frame", row.names = c(NA, 
-16L))

我检查了之前所有的答案，但我被卡住了，我真的不知道是否可以做到这一点，这可能非常简单，所以如果这不是一个正确的问题，我已经道歉了。如果你给我一个提示，我会自己做