我想从两种不同类型的DataFrame创建一个DataFrame，并带有条件并保留额外的列。我的第一个DataFrame是：
sample_id motif chromosome position
1 CT-G.A chr1 7300
1 TA-C.C chr1 1000
1 TC-G.C chr2 1200
1 TC-G.C chr2 3000
2 CG-A.T chr2 12898
2 CA-G.T chr2 234235
，第二个DataFrame是：
geneID chromosome start end
E1 chr1 100 10300
E2 chr1 1100 20122
E3 chr2 1200 2000
E4 chr2 400 234236
E5 chr2 12000 20000
然后我想创建一个具有以下条件的DataFrame：
if (first$chromosome == second$chromosome & second$start<= first$position <= second$end)
sample_id E1,CT-G.A E1,TA-C.C E1,TC-G.C E1,TC-G.C E1,CG-A.T E1,CA-G.T E2,CT-G.A E2,TA-C.C E2,TC-G.C E2,CG-A.T E2,CA-G.T E3,CT-G.A E3,TA-C.C E3,TC-G.C E3,CG-A.T E3,CA-G.T E4,CT-G.A E4,TA-C.C E4,TC-G.C E4,CG-A.T E4,CA-G.T E5,CT-G.A E5,TA-C.C E5,TC-G.C E5,CG-A.T E5,CA-G.T E6,CT-G.A E6,TA-C.C E6,TC-G.C E6,CG-A.T E6,CA-G.T
1 1 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0
2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0
答案 0 :(得分：1)
这会奏效。但是，如果你这样做，你可能想要考虑你的列标题。
library(dplyr)
library(tidyr)
df1 %>% inner_join(df2, "chromosome") %>%
mutate(geneID_motif = paste(geneID, motif, sep = ","),
n = if_else(position >= start & position <= end, 1, 0)) %>%
select(sample_id, geneID_motif, n) %>%
group_by(sample_id, geneID_motif) %>%
summarise(n = sum(n)) %>%
spread(key = geneID_motif, value = n, fill = 0)
# A tibble: 2 x 14
# Groups: sample_id [2]
sample_id `E1,CT-G.A` `E1,TA-C.C` `E2,CT-G.A` `E2,TA-C.C` `E3,CA-G.T` `E3,CG-A.T` `E3,TC-G.C` `E4,CA-G.T` `E4,CG-A.T` `E4,TC-G.C`
<int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 1 1.00 1.00 1.00 0 0 0 1.00 0 0 2.00
2 2 0 0 0 0 0 0 0 1.00 1.00 0
# ... with 3 more variables: `E5,CA-G.T` <dbl>, `E5,CG-A.T` <dbl>, `E5,TC-G.C` <dbl>
数据：
df1 <-
structure(
list(
sample_id = c(1L, 1L, 1L, 1L, 2L, 2L),
motif = c("CT-G.A", "TA-C.C", "TC-G.C", "TC-G.C", "CG-A.T", "CA-G.T"),
chromosome = c("chr1", "chr1", "chr2", "chr2", "chr2", "chr2"),
position = c(7300L, 1000L, 1200L, 3000L, 12898L, 234235L)
),
.Names = c("sample_id", "motif", "chromosome", "position"),
class = "data.frame",
row.names = c(NA,-6L)
)
df2 <-
structure(
list(
geneID = c("E1", "E2", "E3", "E4", "E5"),
chromosome = c("chr1", "chr1", "chr2", "chr2", "chr2"),
start = c(100L, 1100L, 1200L,400L, 12000L),
end = c(10300L, 20122L, 2000L, 234236L, 20000L)
),
.Names = c("geneID", "chromosome", "start", "end"),
class = "data.frame",
row.names = c(NA,-5L)
)
答案 1 :(得分：1)
希望这有帮助！
library(dplyr)
library(tidyr)
df1 %>%
crossing(df2) %>%
mutate(geneID_motif = paste(geneID, motif, sep=","),
flag=ifelse(start <= position & position <= end & chromosome1 == chromosome2, 1, 0)) %>%
select(sample_id, geneID_motif, flag) %>%
group_by(sample_id, geneID_motif) %>%
summarise(flag=as.integer(sum(flag))) %>%
spread(geneID_motif, flag) %>%
replace(is.na(.),0) %>%
data.frame(check.names=FALSE)
输出是：
sample_id E1,CA-G.T E1,CG-A.T E1,CT-G.A E1,TA-C.C E1,TC-G.C E2,CA-G.T E2,CG-A.T E2,CT-G.A E2,TA-C.C E2,TC-G.C
1 1 0 0 1 1 0 0 0 1 0 0
2 2 0 0 0 0 0 0 0 0 0 0
E3,CA-G.T E3,CG-A.T E3,CT-G.A E3,TA-C.C E3,TC-G.C E4,CA-G.T E4,CG-A.T E4,CT-G.A E4,TA-C.C E4,TC-G.C E5,CA-G.T
1 0 0 0 0 1 0 0 0 0 2 0
2 0 0 0 0 0 1 1 0 0 0 0
E5,CG-A.T E5,CT-G.A E5,TA-C.C E5,TC-G.C
1 0 0 0 0
2 1 0 0 0
示例数据：
df1 <- structure(list(sample_id = c(1L, 1L, 1L, 1L, 2L, 2L), motif = c("CT-G.A",
"TA-C.C", "TC-G.C", "TC-G.C", "CG-A.T", "CA-G.T"), chromosome1 = c("chr1",
"chr1", "chr2", "chr2", "chr2", "chr2"), position = c(7300L,
1000L, 1200L, 3000L, 12898L, 234235L)), .Names = c("sample_id",
"motif", "chromosome1", "position"), class = "data.frame", row.names = c(NA,
-6L))
df2 <- structure(list(geneID = c("E1", "E2", "E3", "E4", "E5"), chromosome2 = c("chr1",
"chr1", "chr2", "chr2", "chr2"), start = c(100L, 1100L, 1200L,
400L, 12000L), end = c(10300L, 20122L, 2000L, 234236L, 20000L
)), .Names = c("geneID", "chromosome2", "start", "end"), class = "data.frame", row.names = c(NA,
-5L))