Conditional Insert of Rows

Question

I have a unique dataset, a portion of which can be reproduced using:

data <- textConnection("SNP_Pres,Chr_N,BP_A1F,A1_Beta,A2_SE,ForSortSNP,SortOrder
rs122,13,100461219,C,T,rs122,6
1,16362,0.8701,-0.0048,0.0056,rs122,7
1,19509,0.546015137607046,-0.0033,0.0035,rs122,8
1,17218,0.1539,-0.004,0.013,rs122,9
rs142,13,61952115,G,T,rs142,6
1,16387,0.1295,0.0044,0.0057,rs142,7
1,17218,0.8454,0.006,0.013,rs142,9
rs160,13,100950452,C,T,rs160,6
1,16387,0.549,-0.0021,0.0035,rs160,7
1,19509,0.519102731537216,0.003,0.0027,rs160,8
rs298,13,66664221,C,G,rs298,6
1,19509,0.308290808358246,-0.0032,0.0033,rs298,8
1,17218,0.7227,0.022,0.01,rs298,9")
mydata <- read.csv(data, header = T, sep = ",", stringsAsFactors=FALSE)

It is formatted for use in a program that requires holding spots for missing data entries. In this case, a missing entry is indicated by a numeric skip in the Sort Order column. An entry is complete if the column descends 6 - 7 - 8 - 9, with a new entry beginning again with 6.

I need a way to read through the data file, and insert a row of zeros for each missing entry, so that the file looks like this:

data <- textConnection("SNP_Pres,Chr_N,BP_A1F,A1_Beta,A2_SE,ForSortSNP,SortOrder
rs122,13,100461219,C,T,rs122,6
1,16362,0.8701,-0.0048,0.0056,rs122,7
1,19509,0.546015137607046,-0.0033,0.0035,rs122,8
1,17218,0.1539,-0.004,0.013,rs122,9
rs142,13,61952115,G,T,rs142,6
1,16387,0.1295,0.0044,0.0057,rs142,7
0,0,0,0,0,rs142,8
1,17218,0.8454,0.006,0.013,rs142,9
rs160,13,100950452,C,T,rs160,6
1,16387,0.549,-0.0021,0.0035,rs160,7
1,19509,0.519102731537216,0.003,0.0027,rs160,8
0,0,0,0,0,rs160,9
rs298,13,66664221,C,G,rs298,6
0,0,0,0,0,rs289, 7
1,19509,0.308290808358246,-0.0032,0.0033,rs298,8
1,17218,0.7227,0.022,0.01,rs298,9")
mydata <- read.csv(data, header = T, sep = ",", stringsAsFactors=FALSE)

Ultimately, the last two columns, ForSortSNP and SortOrder will be deleted from the data file, but they are included now for convenience's sake. Any suggestions are greatly appreicated.

Answer 1

Here is a solution using the expand.grid and merge functions.

grid <- with(mydata, expand.grid(ForSortSNP=unique(ForSortSNP), SortOrder=unique(SortOrder)))
complete <- merge(mydata, grid, all=TRUE, sort=FALSE)
complete[is.na(complete)] <- 0 # replace NAs with 0's
complete <- complete[order(complete$ForSortSNP, complete$SortOrder), ] # re-sort