発現量のデータを読み込む

csv形式ならread.csvで、タブ区切りならread.tableで読み込みます。

ppm <- read.csv("ppm.csv", as.is = T)
head(ppm)

A data.frame: 6 × 6

	reference_id	Fe_control_1	Fe_left_3	Fe_right_4	Fe_starv_5	annotation
	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<chr>
1	AT1G01010.1	18.914394	22.617745	29.5624070	21.329631	NAC domain containing protein 1
2	AT1G01020.1	13.331731	7.539248	8.7370676	9.057788	Arv1-like protein
3	AT1G01020.2	12.165205	6.954307	8.4976959	8.181228	Arv1-like protein
4	AT1G01030.1	1.333173	2.794721	0.9574869	1.363538	AP2/B3-like transcriptional factor family protein
5	AT1G01040.1	55.659978	50.629953	51.9436624	51.522259	dicer-like 1
6	AT1G01040.2	53.826865	49.330083	50.5074321	49.379556	dicer-like 1

長さのデータを読み込む

データベースから出力したファイルを読み込みます。こちらはタブ区切りなのでread.tableを使います。 psql -h gerbera pothos -AtF $'\t' -c "select reference_id, length(sequence) from ref_ath10" >length.txt

len <- read.table("length.txt", as.is = T)
head(len)

A data.frame: 6 × 2

	V1	V2
	<chr>	<int>
1	ATMG00130.1	366
2	ATCG00860.1	6885
3	ATMG00516.1	318
4	ATCG00670.1	591
5	ATCG01020.1	159
6	ATMG00900.1	771

表を結合する

遺伝子番号をキーにして二つのデータを結合します。

d <- merge(ppm, len, by.x = 1, by.y = 1)
head(d)

A data.frame: 6 × 7

	reference_id	Fe_control_1	Fe_left_3	Fe_right_4	Fe_starv_5	annotation	V2
	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<chr>	<int>
1	AT1G01010.1	18.914394	22.617745	29.5624070	21.329631	NAC domain containing protein 1	1688
2	AT1G01020.1	13.331731	7.539248	8.7370676	9.057788	Arv1-like protein	1623
3	AT1G01020.2	12.165205	6.954307	8.4976959	8.181228	Arv1-like protein	1085
4	AT1G01030.1	1.333173	2.794721	0.9574869	1.363538	AP2/B3-like transcriptional factor family protein	1905
5	AT1G01040.1	55.659978	50.629953	51.9436624	51.522259	dicer-like 1	6251
6	AT1G01040.2	53.826865	49.330083	50.5074321	49.379556	dicer-like 1	5877

長さで割る

d[,2:(dim(d)[2] - 2)] <- d[,2:(dim(d)[2] - 2)] / d[,7] * 1000
head(d)

A data.frame: 6 × 7

	reference_id	Fe_control_1	Fe_left_3	Fe_right_4	Fe_starv_5	annotation	V2
	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<chr>	<int>
1	AT1G01010.1	11.2052096	13.399138	17.5132743	12.636037	NAC domain containing protein 1	1688
2	AT1G01020.1	8.2142522	4.645255	5.3832826	5.580892	Arv1-like protein	1623
3	AT1G01020.2	11.2121703	6.409499	7.8319778	7.540303	Arv1-like protein	1085
4	AT1G01030.1	0.6998284	1.467045	0.5026178	0.715768	AP2/B3-like transcriptional factor family protein	1905
5	AT1G01040.1	8.9041718	8.099497	8.3096564	8.242243	dicer-like 1	6251
6	AT1G01040.2	9.1589017	8.393752	8.5940841	8.402171	dicer-like 1	5877

ファイルに書き出す

write.csv(d[,-dim(d)[2]], "fpkm.csv", row.names = FALSE)