CODEWITHSUNDEEP
rreshape2data-wranglingwrangle
Lu_Ste
Lu_Ste

Reputation: 21

Wrangle dataframe in R, possibly with dcast

I have a data.frame quite large that I have to wrangle it a bit. the current structure is:

V1   V2 V3 V4 V5         V6        V7         V8         ...   Vn         Vn+1
chr1  1 A  T  sample_1   value_1   sample_2   value_4   ...   sample_n   value_7 
chr1 40 T  C  sample_1   value_2   sample_2   value_5   ...   sample_n   value_8
chr1 60 A  T  sample_1   value_3   sample_2   value_6   ...   sample_n   value_9
.
.
.
chrX 160 A  T  sample_1   value_x   sample_2   value_y   ...  sample_n value_ni

e.g. for the data_frame:

df <- structure(list(V1 = c(10L, 10L, 10L, 10L, 10L, 10L), V2 = c(3387501L, 
4174142L, 6419754L, 6419765L, 6419897L, 6419912L), V3 = c("T", 
"A", "C", "T", "G", "A"), V4 = c("A", 
"T", "A", "A", "C", "G"), V5 = c("LP2000748-DNA_H02", 
"LP2000748-DNA_H02", "LP2000748-DNA_H02", "LP2000748-DNA_H02", 
"LP2000748-DNA_H02", "LP2000748-DNA_H02"), V6 = c("0/0", "0/0", 
"1/1", "0/0", "0/0", "0/0"), V7 = c("LP2000748-DNA_A03", "LP2000748-DNA_A03", 
"LP2000748-DNA_A03", "LP2000748-DNA_A03", "LP2000748-DNA_A03", 
"LP2000748-DNA_A03"), V8 = c("0/0", "0/0", "1/1", "0/1", "0/0", 
"0/0"), V9 = c("LP2000795-DNA_B01", "LP2000795-DNA_B01", "LP2000795-DNA_B01", 
"LP2000795-DNA_B01", "LP2000795-DNA_B01", "LP2000795-DNA_B01"
), V10 = c("0/0", "0/0", "1/1", "0/0", "0/0", "0/0")), row.names = c(NA, 
-6L), class = c("data.table", "data.frame"))

What I'd like to have in the end is a table like this:

V1   V2 V3 V4 sample_1   sample_2   ...   sample_n    
chr1  1 A  T   value_1    value_4   ...    value_7 
chr1 40 T  C   value_2    value_5   ...    value_8
chr1 60 A  T   value_3    value_6   ...    value_9
.
.
.
chrX 160 A  T   value_x    value_y   ...  value_ni

What I've tried so far in R is:

samples_data <- seq(from = 5, to = dim(df)[2],by=2) variable_data <- samples_data + 1

new_df <- reshape2::dcast(df, V1 + V2 + V3 ~ colnames(df)[samples_data], value.var= colnames(df)[variable_data])

but I get this error message:

  recursive indexing failed at level 2
In addition: Warning message:
In if (!(value.var %in% names(data))) { :
  the condition has length > 1 and only the first element will be used

Does anyone have any suggestion on how to tackle this problem or on how to reshape the df?

Thanks!

Upvotes: 1

Views: 30

Answers (1)

jay.sf
jay.sf

Reputation: 72919

You probably need to un-nest the data, then use reshape. To un-nest you could use Map to generate a list selecting the first four ID columns and from the rest of the columns a pattern 5,6; 7,8; 9,10. rbind the result and reshape.

cseq <- 5:ncol(df)
tmp <- do.call(rbind, Map(function(x, y) setNames(df[c(1:4, x:y)], 
                                                  c(names(df)[1:4], c("sample", "value"))), 
                   cseq[cseq %% 2 != 0], cseq[cseq %% 2 == 0]))
res <- reshape(tmp, idvar=1:4, timevar="sample", v.names="value", direction="wide")
res
#   V1      V2 V3 V4 value.LP2000748-DNA_H02 value.LP2000748-DNA_A03 value.LP2000795-DNA_B01
# 1 10 3387501  T  A                     0/0                     0/0                     0/0
# 2 10 4174142  A  T                     0/0                     0/0                     0/0
# 3 10 6419754  C  A                     1/1                     1/1                     1/1
# 4 10 6419765  T  A                     0/0                     0/1                     0/0
# 5 10 6419897  G  C                     0/0                     0/0                     0/0
# 6 10 6419912  A  G                     0/0                     0/0                     0/0

Upvotes: 0

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