Some additional options with base R:
url <- "http://cbio.mskcc.org/microrna_data/human_predictions_S_C_aug2010.txt.gz" tmp <- tempfile() ## download.file(url,tmp) ## data <- read.csv( gzfile(tmp), sep="\t", header=TRUE, stringsAsFactors=FALSE) names(data)[1] <- sub("X\\.","",names(data)[1]) ## R> head(data) mirbase_acc mirna_name gene_id gene_symbol transcript_id ext_transcript_id mirna_alignment 1 MIMAT0000062 hsa-let-7a 5270 SERPINE2 uc002vnu.2 NM_006216 uuGAUAUGUUGGAUGAU-GGAGu 2 MIMAT0000062 hsa-let-7a 494188 FBXO47 uc002hrc.2 NM_001008777 uugaUA-UGUU--GGAUGAUGGAGu 3 MIMAT0000062 hsa-let-7a 80025 PANK2 uc002wkc.2 NM_153638 uugauaUGUUGG-AUGAUGGAgu 4 MIMAT0000062 hsa-let-7a 26036 ZNF451 uc003pdp.2 AK027074 uuGAUAUGUUGGAUGAUGGAGu 5 MIMAT0000062 hsa-let-7a 586 BCAT1 uc001rgd.3 NM_005504 uugaUAUGUUGGAUGAUGGAGu 6 MIMAT0000062 hsa-let-7a 22903 BTBD3 uc002wnz.2 NM_014962 uuGAUAUGUUGGAU-GAUGG-AGu alignment gene_alignment mirna_start mirna_end gene_start gene_end 1 | :|: ||:|| ||| |||| aaCGGUGAAAUCU-CUAGCCUCu 2 21 495 516 2 || |||: ::||||||||: acaaAUCACAGUUUUUACUACCUUc 2 19 459 483 3 |::||: |||||||| aauuucAUGACUGUACUACCUga 3 17 77 99 4 || || | | ||||||| ccCUCUAGA---UUCUACCUCa 2 21 1282 1300 5 :|| |: |||||||| guagGUAAAGGAAACUACCUCa 2 19 6410 6431 6 || || ||| || ||||| || uaCUUUAAAACAUAUCUACCAUCu 2 21 2265 2288 genome_coordinates conservation align_score seed_cat energy mirsvr_score 1 [hg19:2:224840068-224840089:-] 0.5684 122 0 -14.73 -0.7269 2 [hg19:17:37092945-37092969:-] 0.6464 140 0 -16.38 -0.1156 3 [hg19:20:3904018-3904040:+] 0.6522 139 0 -16.04 -0.2066 4 [hg19:6:56966300-56966318:+] 0.7627 144 7 -14.51 -0.8609 5 [hg19:12:24964511-24964532:-] 0.6775 150 7 -15.09 -0.2735 6 [hg19:20:11906579-11906602:+] 0.5740 131 0 -12.59 -0.2540
Or, if you are using a Unix-like system, you can get the .txt file (outside of R or using system or system2 from R) as follows:
[ nathan@nrussell tmp]$ url="http://cbio.mskcc.org/microrna_data/human_predictions_S_C_aug2010.txt.gz" [ nathan@nrussell tmp]$ wget "$url" && gunzip human_predictions_S_C_aug2010.txt.gz
and then proceed as above, where you read human_predictions_S_C_aug2010.txt , wherever wget and gunzip ,
data <- read.csv( "~/tmp/human_predictions_S_C_aug2010.txt", stringsAsFactors=FALSE, header=TRUE, sep="\t")
in my case.
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