I have a data frame with the following structure:
> dftest
element seqnames start end width strand tx_id tx_name
1 1 chr19 58858172 58864865 6694 - 36769 NM_130786
2 10 chr8 18248755 18258723 9969 + 16614 NM_000015
3 100 chr20 43248163 43280376 32214 - 37719 NM_000022
4 1000 chr18 25530930 25757445 226516 - 33839 NM_001792
5 10000 chr1 243651535 244006584 355050 - 4182 NM_181690
6 10000 chr1 243663021 244006584 343564 - 4183 NM_005465
1316 100302285 chr12 12264886 12264967 82 + 24050 NR_036052
1317 100302285 chr12 9392066 9392147 82 - 25034 NR_036052
1318 100302285 chr2 232578024 232578105 82 + 5491 NR_036052
1319 100302285 chr5 118310281 118310362 82 + 11128 NR_036052
As an intermediate step I am trying to get rid of the elements, such as "100302285", that are present more than once, but with different "seqnames". Element "10000" would be kept because all "seqnames" are the same. Elements that are present only once are also kept. This is the desired output:
> dftest
element seqnames start end width strand tx_id tx_name
1 1 chr19 58858172 58864865 6694 - 36769 NM_130786
2 10 chr8 18248755 18258723 9969 + 16614 NM_000015
3 100 chr20 43248163 43280376 32214 - 37719 NM_000022
4 1000 chr18 25530930 25757445 226516 - 33839 NM_001792
5 10000 chr1 243651535 244006584 355050 - 4182 NM_181690
6 10000 chr1 243663021 244006584 343564 - 4183 NM_005465
So far I've played with ddply and custom function to include duplicates:
subChr <- function(df)
{
df[duplicated(df$seqnames),]
}
ddply(df, .(element), subChr)
But the result is far from the intended - silly me, it could have not been that simple:
element seqnames start end width strand tx_id tx_name
1 10000 chr1 243663021 244006584 343564 - 4183 NM_005465
2 100302285 chr12 9392066 9392147 82 - 25034 NR_036052
Since this is a step before another ddply, I would be happy with an alternative solution that does this:
ddply(df, .(element), summarize, chromosome=seqnames[1], gene_start=min(start), gene_end=max(end), strand=strand[1])
element chromosome gene_start gene_end strand
1 1 chr19 58858172 58864865 -
2 10 chr8 18248755 18258723 +
3 100 chr20 43248163 43280376 -
4 1000 chr18 25530930 25757445 -
5 10000 chr1 243651535 244006584 -
6 100302285 chr12 9392066 232578105 +
but summarizes element "100302285" for each "seqnames":
element chromosome gene_start gene_end strand
1 1 chr19 58858172 58864865 -
2 10 chr8 18248755 18258723 +
3 100 chr20 43248163 43280376 -
4 1000 chr18 25530930 25757445 -
5 10000 chr1 243651535 244006584 -
6 100302285 chr12 9392066 12264967 +
7 100302285 chr2 232578024 232578105 +
8 100302285 chr5 118310281 118310362 +
Basically summarizing by .element and .seqname, if that makes sense. I have been searching for an answer for sometime now but did not progress much.
Test data:
dftest <- structure(list(element = c("1", "10", "100", "1000", "10000",
"10000", "100302285", "100302285", "100302285", "100302285"),
seqnames = c("chr19", "chr8", "chr20", "chr18", "chr1", "chr1",
"chr12", "chr12", "chr2", "chr5"), start = c(58858172L, 18248755L,
43248163L, 25530930L, 243651535L, 243663021L, 12264886L,
9392066L, 232578024L, 118310281L), end = c(58864865L, 18258723L,
43280376L, 25757445L, 244006584L, 244006584L, 12264967L,
9392147L, 232578105L, 118310362L), width = c(6694L, 9969L,
32214L, 226516L, 355050L, 343564L, 82L, 82L, 82L, 82L), strand = c("-",
"+", "-", "-", "-", "-", "+", "-", "+", "+"), tx_id = c(36769L,
16614L, 37719L, 33839L, 4182L, 4183L, 24050L, 25034L, 5491L,
11128L), tx_name = c("NM_130786", "NM_000015", "NM_000022",
"NM_001792", "NM_181690", "NM_005465", "NR_036052", "NR_036052",
"NR_036052", "NR_036052")), .Names = c("element", "seqnames",
"start", "end", "width", "strand", "tx_id", "tx_name"), class = "data.frame", row.names = c(1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L))
Answering your first question: If you like, here's a data.table solution:
require(data.table)
dt <- data.table(dftest, key="element")
dt.out <- dt[, .SD[length(table(seqnames)) == 1],by=c("element")]
> dt.out
# element seqnames start end width strand tx_id tx_name
# 1: 1 chr19 58858172 58864865 6694 - 36769 NM_130786
# 2: 10 chr8 18248755 18258723 9969 + 16614 NM_000015
# 3: 100 chr20 43248163 43280376 32214 - 37719 NM_000022
# 4: 1000 chr18 25530930 25757445 226516 - 33839 NM_001792
# 5: 10000 chr1 243651535 244006584 355050 - 4182 NM_181690
# 6: 10000 chr1 243663021 244006584 343564 - 4183 NM_005465
And if you prefer the plyr solution:
require(plyr)
out <- ddply(dftest, .(element), function(x) {
if( length(table(x$seqnames)) == 1) {
x
}
})
# element seqnames start end width strand tx_id tx_name
# 1 1 chr19 58858172 58864865 6694 - 36769 NM_130786
# 2 10 chr8 18248755 18258723 9969 + 16614 NM_000015
# 3 100 chr20 43248163 43280376 32214 - 37719 NM_000022
# 4 1000 chr18 25530930 25757445 226516 - 33839 NM_001792
# 5 10000 chr1 243651535 244006584 355050 - 4182 NM_181690
# 6 10000 chr1 243663021 244006584 343564 - 4183 NM_005465
Edit: For your second question, basically, in addition to the old solution, you just want to return the first row when your first condition is not satisfied.
plyr solution: (without summarise)
out <- ddply(dftest, .(element), function(x) {
if (length(table(x$seqnames)) == 1) {
x
} else {
x[1, ]
}
})
> out
# element seqnames start end width strand tx_id tx_name
# 1 1 chr19 58858172 58864865 6694 - 36769 NM_130786
# 2 10 chr8 18248755 18258723 9969 + 16614 NM_000015
# 3 100 chr20 43248163 43280376 32214 - 37719 NM_000022
# 4 1000 chr18 25530930 25757445 226516 - 33839 NM_001792
# 5 10000 chr1 243651535 244006584 355050 - 4182 NM_181690
# 6 10000 chr1 243663021 244006584 343564 - 4183 NM_005465
# 7 100302285 chr12 12264886 12264967 82 + 24050 NR_036052
data.table solution.
dt <- data.table(dftest, key="element")
dt[, .SD[(if(length(table(seqnames)) == 1) seq_len(.N) else 1)], by = element]
> dt.out
# element seqnames start end width strand tx_id tx_name
# 1: 1 chr19 58858172 58864865 6694 - 36769 NM_130786
# 2: 10 chr8 18248755 18258723 9969 + 16614 NM_000015
# 3: 100 chr20 43248163 43280376 32214 - 37719 NM_000022
# 4: 1000 chr18 25530930 25757445 226516 - 33839 NM_001792
# 5: 10000 chr1 243651535 244006584 355050 - 4182 NM_181690
# 6: 10000 chr1 243663021 244006584 343564 - 4183 NM_005465
# 7: 100302285 chr12 12264886 12264967 82 + 24050 NR_036052
来源：https://stackoverflow.com/questions/14590127/exclude-duplicate-values-in-certain-columns-using-ddply