집계를 사용하고 값 열만 얻는 방법?

Question

숫자 집합에서 집계 함수를 사용하려고합니다. 집계가 내가 원하는 함수를 계산 한 후에, 나는 csv 파일에 출력을 썼다. 그러나이 CSV 파일은 값 테이블과 카운트 테이블로 구성됩니다. 카운트 테이블을 제거하고 싶습니다. 총계의 짤막음과 전체 {STATS} 매뉴얼을 확인했습니다. 그러나 나를 위해 이것을하는 매개 변수를 찾을 수 없습니다.

그래서 질문입니다. 집계에 내가 값 열만 있고 집계 값을 원하지 않는다는 것을 어떻게 알 수 있습니까?

집계 함수는 내가 쓴 :

sdint<-aggregate(assayData(object)$intensity[,sample], 
       by = list(assayData(object)$states[,sample]), 
       sd, 
       na.rm=TRUE) 

데이터 난`는 사용 : Data

내가 원하는 출력 : 내가 가진

0.576778569 
0.300184855 
0.303007167 
0.339285757 
0.309673603 
0.345517885 
0.218438482 
0.274175334 
0.322680676 
0.342179188 
0.321930905 
0.391558862 
0.365504912 
0.37906546 
0.425801585 
0.348280535 
0.330063333 
0.388093547 
0.262649566 
0.202235805 
0.294549104 
0.206346439 
0.190531238 
0.227790818 
0.238224514 
0.264646831 
0.286682489 
0.231069902 
0.25936052 
0.363558042 
0.210798912 
0.18124299 
0.438063879 
0.264264297 
0.254382012 
0.464863254 

출력 :

을

1 0.576778569 
2 0.300184855 
3 0.303007167 
4 0.339285757 
5 0.309673603 
6 0.345517885 
7 0.218438482 
8 0.274175334 
9 0.322680676 
10 0.342179188 
11 0.321930905 
12 0.391558862 
13 0.365504912 
14 0.37906546 
15 0.425801585 
16 0.348280535 
17 0.330063333 
18 0.388093547 
19 0.262649566 
20 0.202235805 
21 0.294549104 
22 0.206346439 
23 0.190531238 
24 0.227790818 
25 0.238224514 
26 0.264646831 
27 0.286682489 
28 0.231069902 
29 0.25936052 
30 0.363558042 
31 0.210798912 
32 0.18124299 
33 0.438063879 
34 0.264264297 
35 0.254382012 
36 0.464863254 

왼쪽의 숫자가 표시되지 않아야합니다! CSV 형식으로

마지막 데이터 :

SNP_NAME,x0,x1,y,pos.start,pos.end,chrom,count,copynumber,intensity,allele.B,Lair,uncertain,Count,StandardLairDev,Count,MAX Lair,StandardIntDev,sample_id 
"rs2065525",0,0,0,1896162,3138455,1,11,2,0.855,0,0.425,FALSE,1,0.287467339786124,1,0.999191681792884,1,0.576778568588604,"00_11242T1" 
"rs1694379",0,0,0,3138456,148286049,1,263,2,0.9825,0,0.4758,FALSE,2,0.25066539967999,2,0.999763634558257,2,0.300184854995405,"00_11242T1" 
"rs2027432",0,0,0,148286050,122268329,1,204,2,1.1092,1,0.8893,FALSE,3,0.128285157028804,3,0.999780287813653,3,0.303007166704586,"00_11242T1" 
"rs16747",0,0,0,122268330,121622963,2,475,2,1.0407,0,0.7684,FALSE,4,0.16048988360498,4,0.99988056078919,4,0.339285756513036,"00_11242T1" 
"rs1490265",0,0,0,121622964,67491556,3,136,2,1.0775,1,0.8031,FALSE,5,0.139532962911464,5,0.998567181034836,5,0.309673602648317,"00_11242T1" 
"rs1864668",0,0,0,67491557,99834810,3,262,2,1.0775,0,0.6657,FALSE,6,0.174074950555206,6,0.999664655449619,6,0.345517884636054,"00_11242T1" 
"rs1363207",0,0,0,99834811,182678081,4,270,2,0.883,0,0.5592,FALSE,7,0.22676775183123,7,0.999303463143844,7,0.218438481623468,"00_11242T1" 
"rs1915853",0,0,0,182678082,96069863,4,26,2,0.6829,0,0.7207,FALSE,8,0.147755391322562,8,0.999377450758501,8,0.274175334131741,"00_11242T1" 
"rs40207",0,0,0,96069864,57625291,5,98,2,1.0482,0,0.6674,FALSE,9,0.193783525020888,9,0.99961281189186,9,0.322680675891498,"00_11242T1" 
"rs2041318",0,0,0,57625292,126652199,5,121,2,0.891,1,0.8323,FALSE,10,0.126062170080585,10,0.9997133021412,10,0.34217918778308,"00_11242T1" 
"rs1053110",0,0,0,126652200,90354277,5,93,2,1.0506,0,0.7829,FALSE,11,0.156375642874615,11,0.998198995215151,11,0.32193090491761,"00_11242T1" 
"rs2021899",0,0,0,90354278,85692795,6,410,2,1.0628,1,0.8398,FALSE,12,0.15435382388065,12,0.99993200438923,12,0.391558862043803,"00_11242T1" 
"rs455030",0,0,0,85692796,79407284,7,285,2,1.0871,1,0.8669,FALSE,13,0.132137812936442,13,0.999929485697204,13,0.365504911746432,"00_11242T1" 
"rs1433396",0,0,0,79407285,122076407,8,212,2,0.9334,0,0.4804,FALSE,14,0.263530051339396,14,0.999654307577374,14,0.379065459942171,"00_11242T1" 
"rs755520",0,0,0,122076408,129448086,8,15,2,1.4429,0,0.4941,FALSE,15,0.149143991344688,15,0.914078743250954,15,0.425801584614172,"00_11242T1" 
"rs1735173",0,0,0,129448087,73161466,8,33,2,0.9364,0,0.4316,FALSE,16,0.278273609876866,16,0.996653200437299,16,0.348280535013844,"00_11242T1" 
"rs2026349",0,0,0,73161467,66782116,9,71,2,1.1968,1,0.8239,FALSE,17,0.189895617817744,17,0.999776858536029,17,0.330063332737979,"00_11242T1" 
"rs735107",0,0,0,66782117,130050087,9,117,2,0.9506,1,0.8461,FALSE,18,0.141861258733706,18,0.999894912286988,18,0.388093547266615,"00_11242T1" 
"rs766374",0,0,0,130050088,68176968,9,17,2,1.0932,1,0.8713,FALSE,19,0.0910714792585353,19,0.997719201852223,19,0.262649566352474,"00_11242T1" 
"rs880340",0,0,0,68176969,67402459,10,248,2,1.068,0,0.4195,FALSE,20,0.269922761074577,20,0.999527729786447,20,0.202235805019638,"00_11242T1" 
"rs4430531",0,0,0,67402460,67321605,11,229,2,1.1385,1,0.8932,FALSE,21,0.123084967048419,21,0.999592791631743,21,0.294549103735107,"00_11242T1" 
"rs7960480",0,0,0,67321606,74655759,12,285,2,1.0545,1,0.8229,FALSE,22,0.122983123511285,22,0.999569526493407,22,0.206346438819543,"00_11242T1" 
"rs14067",0,0,0,74655760,65198000,13,187,2,1.1479,1,0.8936,FALSE,23,0.118977461806947,23,0.999132908666796,23,0.190531237977798,"00_11242T1" 
"rs1989749",0,0,0,65198001,62810767,14,210,2,0.9512,0,0.5011,FALSE,24,0.243205200245574,24,0.999570632007492,24,0.22779081826097,"00_11242T1" 
"rs1192113",0,0,0,62810768,49992524,15,201,2,0.9459,0,0.5006,FALSE,25,0.242235554332421,25,0.999923600003544,25,0.238224514088702,"00_11242T1" 
"rs869048",0,0,0,49992525,44973166,16,197,2,1.14,1,0.8493,FALSE,26,0.113266709360598,26,0.999410137369512,26,0.26464683057347,"00_11242T1" 
"rs3785513",0,0,0,44973167,40857471,17,159,2,1.0119,0,0.4846,FALSE,27,0.247823361318723,27,0.999773260918777,27,0.286682489405067,"00_11242T1" 
"rs420905",0,0,0,40857472,9614641,18,22,2,0.8881,0,0.7783,FALSE,28,0.143466524230892,28,0.989549332985043,28,0.231069902005914,"00_11242T1" 
"rs1805272",0,0,0,9614642,38052783,18,148,2,0.8881,0,0.5326,FALSE,29,0.223315888643138,29,0.998876808487203,29,0.259360520111394,"00_11242T1" 
"rs3499",0,0,0,38052784,31952708,19,149,2,1.0146,0,0.4964,FALSE,30,0.234643478722549,30,0.999581141159297,30,0.363558042382673,"00_11242T1" 
"rs912239",0,0,0,31952709,39291277,20,130,2,1.1629,1,0.891,FALSE,31,0.141976210855505,31,0.999162417982582,31,0.210798912384771,"00_11242T1" 
"rs2839377",0,0,0,39291278,31199103,21,103,2,0.9569,0,0.5286,FALSE,32,0.234526243870833,32,0.999309316327552,32,0.181242989596378,"00_11242T1" 
"rs10451",0,0,0,31199104,26461186,22,121,2,0.9089,0,0.4561,FALSE,33,0.261911141225885,33,0.999345284476758,33,0.438063878776732,"00_11242T1" 
"rs6780",0,0,0,26461187,70501188,98,125,2,1.1575,1,0.9065,FALSE,34,0.132476526665054,34,0.999987049231316,34,0.264264297319435,"00_11242T1" 
"rs2032438",0,0,0,70501189,76057512,98,179,2,1.0443,1,0.8159,FALSE,35,0.128901714920779,35,0.999765208281892,35,0.254382011767866,"00_11242T1" 
"rs31185",0,0,0,76057513,23098508,99,18,2,0.9412,-4,NA,FALSE,36,0.228356984022432,36,0.993785747186676,36,0.464863253679381,"00_11242T1" 

Answer 1

이 write.csv의 기능입니다. 호출에 row.names=FALSE 매개 변수를 추가하십시오.