How do I subset a data.table based on another data.table?

I am trying to get my head around how to use data.tables. It is not going well.

I have a large data.table with a bunch of retus and AUM. I subsetted that data.table into two data.tables, one with retus, and one with AUM. I now want to subset the retus data.table, to get only the retus from funds with AUM less than the 50th percentile.

To give you an idea, this is my code:

fundDetails <- data.table(read.table("Fund_Deets.csv", sep = ",", fill = TRUE, quote=""", header=TRUE))
fundNAV <- data.table(read.table("NAV_AUM.csv", sep = ",", fill = TRUE, quote=""", header=TRUE))

allFundDetails <- fundDetails[Currency == 'USD']
allFundNAV <- fundNAV[Fund.ID %in% allFundDetails$Fund.ID]
allFundAUM <- allFundNAV[Type == 'AUM', -c(1,3), with = FALSE]
allFundAUM <- setnames(data.table(t(sapply(allFundAUM[,-1, with = FALSE],as.numeric))), as.character(allFundAUM$Fund.ID))
allFundRetus <- allFundNAV[Type == 'Retu', -c(1,3), with = FALSE]
allFundRetus <- setnames(data.table(t(sapply(allFundRetus[,-1, with = FALSE],as.numeric)/100)), as.character(allFundRetus$Fund.ID))
smallFundRetus <- data.table(sapply(allFundRetus, function(x) rep(NA, length(x))))

This Produces the following three tables (smallFundRetus is obviously just NA's):

> allFundAUM[,1:10, with = FALSE]
     33992 33261 38102 33264 33275 5606 41695 40483 41526 45993
  1:    NA    NA    NA    NA    NA   NA    NA    NA     1    27
  2:    NA    NA    NA    NA    NA   NA   117    NA     1    27
  3:    NA    NA    NA    NA    NA   NA   120    NA     1    27
  4:    NA    NA    NA    NA    NA   NA   133    NA     1    27
  5:    NA    NA    NA    NA    NA   NA   146    NA     1    29
 ---                                                           
260:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
261:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
262:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
263:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
264:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
> allFundRetus[,1:10, with = FALSE]
     33992 33261 38102 33264 33275 5606   41695 40483   41526   45993
  1:    NA    NA    NA    NA    NA   NA      NA    NA  0.0188 -0.0116
  2:    NA    NA    NA    NA    NA   NA -0.0315    NA -0.0120  0.0134
  3:    NA    NA    NA    NA    NA   NA -0.0978    NA -0.0908 -0.0206
  4:    NA    NA    NA    NA    NA   NA -0.0445    NA -0.0269 -0.0287
  5:    NA    NA    NA    NA    NA   NA  0.0139    NA  0.0298 -0.0141
 ---                                                                 
260:    NA    NA    NA    NA    NA   NA      NA    NA      NA      NA
261:    NA    NA    NA    NA    NA   NA      NA    NA      NA      NA
262:    NA    NA    NA    NA    NA   NA      NA    NA      NA      NA
263:    NA    NA    NA    NA    NA   NA      NA    NA      NA      NA
264:    NA    NA    NA    NA    NA   NA      NA    NA      NA      NA
> smallFundRetus[,1:10, with = FALSE]
     33992 33261 38102 33264 33275 5606 41695 40483 41526 45993
  1:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
  2:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
  3:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
  4:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
  5:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
 ---                                                           
260:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
261:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
262:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
263:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
264:    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA

for (i in 1:nrow(allFundRetus)){
  theSubset <- as.vector(allFundRetus[i,] <= as.numeric(quantile(allFundAUM[i,], .5, na.rm = TRUE)))
  theSubset[is.na(theSubset)] <- FALSE
  theSubset <- colnames(allFundRetus)[theSubset]
  smallFundRetus[i,theSubset, with = FALSE] = allFundRetus[i,theSubset, with = FALSE]
}

I am trying to subset using this for loop (using a for loop in an attempt to debug):

for (i in 1:nrow(allFundRetus)){
  theSubset <- as.vector(allFundRetus[i,] <= as.numeric(quantile(allFundAUM[i,], .5, na.rm = TRUE)))
  theSubset[is.na(theSubset)] <- FALSE
  theSubset <- colnames(allFundRetus)[theSubset]
  smallFundRetus[i,theSubset, with = FALSE] = allFundRetus[i,theSubset, with = FALSE]
}

This produces an error:

Error in `[<-.data.table`(`*tmp*`, i, theSubset, with = FALSE, value = list( : 
  unused argument (with = FALSE)

I tried removing the 'with' part, but this spits out a bunch of waings:

> waings()
Waing messages:
1: In `[<-.data.table`(`*tmp*`, i, theSubset, value = c("41526",  ... :
  Supplied 3020 items to be assigned to 1 items of column '41526' (3019 unused)
2: In `[<-.data.table`(`*tmp*`, i, theSubset, value = c("41526",  ... :
  Supplied 3020 items to be assigned to 1 items of column '45993' (3019 unused)
3: In `[<-.data.table`(`*tmp*`, i, theSubset, value = c("41526",  ... :
  Supplied 3020 items to be assigned to 1 items of column '45994' (3019 unused)
4: In `[<-.data.table`(`*tmp*`, i, theSubset, value = c("41526",  ... :

I am confused on how to do this. Any ideas on how I can subset the second data.table by the subset on the first?