Dear Jim,
It works great. I appreciate your help.
Sincerely,
Alex
On 6/7/07, jim holtman <[EMAIL PROTECTED]> wrote:
>
> I took your data and duped the data line so I had 100,000 rows and it took
> 40 seconds to read in when specifying colClasses
>
> > system.time(x <- read.table('/tempxx.txt',
> header=TRUE,colClasses=c('factor', rep('numeric',49))))
> user system elapsed
> 40.98 0.46 42.39
> > str(x)
> 'data.frame ': 102272 obs. of 50 variables:
> $ ID : Factor w/ 1 level
> "SNP_A-1780271": 1 1 1 1 1 1 1 1 1 1 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_A09_50156.cel : num 1.86 1.86 1.86
> 1.86 1.86 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_A11_50188.cel : num 1.51 1.51 1.51
> 1.51 1.51 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_A12_50204.cel : num 1.73 1.73 1.73
> 1.73 1.73 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_B09_50158.cel : num 1.53 1.53 1.53
> 1.53 1.53 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_C01_50032.cel : num 1.66 1.66 1.66
> 1.66 1.66 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_C12_50208.cel : num 1.47 1.47 1.47
> 1.47 1.47 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_D03_50066.cel : num 2.16 2.16 2.16
> 2.16 2.16 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_D08_50146.cel : num 1.78 1.78 1.78
> 1.78 1.78 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_F03_50070.cel : num 1.60 1.60 1.60
> 1.60 1.60 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_F12_50214.cel : num 2.16 2.16 2.16
> 2.16 2.16 ...
> $ AIRNS_p_Sty5_Mapping250K_Sty_G09_50168.cel : num 1.98 1.98 1.98
> 1.98 1.98 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_B04_53892.cel : num 2.18 2.18 2.18
> 2.18 2.18 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_B06_53924.cel : num 1.88 1.88 1.88
> 1.88 1.88 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_C05_53910.cel : num 2.15 2.15 2.15
> 2.15 2.15 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_C10_53990.cel : num 1.53 1.53 1.53
> 1.53 1.53 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_D05_53912.cel : num 1.72 1.72 1.72
> 1.72 1.72 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_E01_53850.cel : num 2.23 2.23 2.23
> 2.23 2.23 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_G12_54030.cel : num 1.94 1.94 1.94
> 1.94 1.94 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_H06_53936.cel : num 1.85 1.85 1.85
> 1.85 1.85 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_H08_53968.cel : num 2.16 2.16 2.16
> 2.16 2.16 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_H11_54016.cel : num 2.19 2.19 2.19
> 2.19 2.19 ...
> $ DOLCE_p_Sty7_Mapping250K_Sty_H12_54032.cel : num 2.03 2.03 2.03
> 2.03 2.03 ...
> $ GUSTO_p_Sty20_Mapping250K_Sty_C08_81736.cel : num 2.67 2.67 2.67
> 2.67 2.67 ...
> $ GUSTO_p_Sty20_Mapping250K_Sty_E03_81660.cel : num 2.74 2.74 2.74
> 2.74 2.74 ...
> $ GUSTO_p_Sty20_Mapping250K_Sty_H02_81650.cel : num 2.08 2.08 2.08
> 2.08 2.08 ...
> $ HEWED_p_250KSty_Plate_20060123_GOOD_B01_46246.cel: num 3.21 3.21 3.21
> 3.21 3.21 ...
> $ HEWED_p_250KSty_Plate_20060123_GOOD_C06_46328.cel: num 2.1 2.1 2.1 2.1
> 2.1 ...
> $ HEWED_p_250KSty_Plate_20060123_GOOD_F02_46270.cel: num 2.15 2.15 2.15
> 2.15 2.15 ...
> $ HEWED_p_250KSty_Plate_20060123_GOOD_G04_46304.cel: num 3.52 3.52 3.52
> 3.52 3.52 ...
> $ HOCUS_p_Sty4_Mapping250K_Sty_B05_55060.cel : num 1.37 1.37 1.37
> 1.37 1.37 ...
> $ HOCUS_p_Sty4_Mapping250K_Sty_B12_55172.cel : num 1.66 1.66 1.66
> 1.66 1.66 ...
> $ HOCUS_p_Sty4_Mapping250K_Sty_E05_55066.cel : num 3.16 3.16 3.16
> 3.16 3.16 ...
> $ SOARS_p_Sty23_Mapping250K_Sty_B07_89024.cel : num 2.09 2.09 2.09
> 2.09 2.09 ...
> $ SOARS_p_Sty23_Mapping250K_Sty_C01_88930.cel : num 1.87 1.87 1.87
> 1.87 1.87 ...
> $ SOARS_p_Sty23_Mapping250K_Sty_C11_89090.cel : num 1.90 1.90 1.90
> 1.90 1.90 ...
> $ SOARS_p_Sty23_Mapping250K_Sty_F07_89032.cel : num 1.81 1.81 1.81
> 1.81 1.81 ...
> $ SOARS_p_Sty23_Mapping250K_Sty_H08_89052.cel : num 1.82 1.82 1.82
> 1.82 1.82 ...
> $ SOARS_p_Sty23_Mapping250K_Sty_H10_89084.cel : num 2.26 2.26 2.26
> 2.26 2.26 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_A04_54082.cel : num 1.93 1.93 1.93
> 1.93 1.93 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_A07_54130.cel : num 1.68 1.68 1.68
> 1.68 1.68 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_B08_54148.cel : num 1.34 1.34 1.34
> 1.34 1.34 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_D01_54040.cel : num 1.57 1.57 1.57
> 1.57 1.57 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_D05_54104.cel : num 1.72 1.72 1.72
> 1.72 1.72 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_E04_54090.cel : num 1.95 1.95 1.95
> 1.95 1.95 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_E12_54218.cel : num 1.44 1.44 1.44
> 1.44 1.44 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_G01_54046.cel : num 2.22 2.22 2.22
> 2.22 2.22 ...
> $ VINOS_p_Sty8_Mapping250K_Sty_G12_54222.cel : num 1.76 1.76 1.76
> 1.76 1.76 ...
> $ VOLTS_p_Sty9_Mapping250K_Sty_G09_57916.cel : num 2.05 2.05 2.05
> 2.05 2.05 ...
> $ VOLTS_p_Sty9_Mapping250K_Sty_H12_57966.cel : num 2.64 2.64 2.64
> 2.64 2.64 ...
> >
>
>
> On 6/7/07, ssls sddd <[EMAIL PROTECTED]> wrote:
> >
> > Dear Jim,
> >
> > Thanks a lot! The size of the text file is 189,588,541 bytes.
> > It consists of 238305 rows (including the header) and
> > 50 columns (the first column is for ID and the rest for 49 samples).
> >
> > The first row looks like:
> >
> > "ID"
> > AIRNS_p_Sty5_Mapping250K_Sty_A09_50156.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_A11_50188.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_A12_50204.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_B09_50158.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_C01_50032.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_C12_50208.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_D03_50066.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_D08_50146.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_F03_50070.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_F12_50214.cel
> > AIRNS_p_Sty5_Mapping250K_Sty_G09_50168.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_B04_53892.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_B06_53924.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_C05_53910.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_C10_53990.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_D05_53912.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_E01_53850.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_G12_54030.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_H06_53936.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_H08_53968.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_H11_54016.cel
> > DOLCE_p_Sty7_Mapping250K_Sty_H12_54032.cel
> > GUSTO_p_Sty20_Mapping250K_Sty_C08_81736.cel
> > GUSTO_p_Sty20_Mapping250K_Sty_E03_81660.cel
> > GUSTO_p_Sty20_Mapping250K_Sty_H02_81650.cel
> > HEWED_p_250KSty_Plate_20060123_GOOD_B01_46246.cel
> > HEWED_p_250KSty_Plate_20060123_GOOD_C06_46328.cel
> > HEWED_p_250KSty_Plate_20060123_GOOD_F02_46270.cel
> > HEWED_p_250KSty_Plate_20060123_GOOD_G04_46304.cel
> > HOCUS_p_Sty4_Mapping250K_Sty_B05_55060.cel
> > HOCUS_p_Sty4_Mapping250K_Sty_B12_55172.cel
> > HOCUS_p_Sty4_Mapping250K_Sty_E05_55066.cel
> > SOARS_p_Sty23_Mapping250K_Sty_B07_89024.cel
> > SOARS_p_Sty23_Mapping250K_Sty_C01_88930.cel
> > SOARS_p_Sty23_Mapping250K_Sty_C11_89090.cel
> > SOARS_p_Sty23_Mapping250K_Sty_F07_89032.cel
> > SOARS_p_Sty23_Mapping250K_Sty_H08_89052.cel
> > SOARS_p_Sty23_Mapping250K_Sty_H10_89084.cel
> > VINOS_p_Sty8_Mapping250K_Sty_A04_54082.cel
> > VINOS_p_Sty8_Mapping250K_Sty_A07_54130.cel
> > VINOS_p_Sty8_Mapping250K_Sty_B08_54148.cel
> > VINOS_p_Sty8_Mapping250K_Sty_D01_54040.cel
> > VINOS_p_Sty8_Mapping250K_Sty_D05_54104.cel
> > VINOS_p_Sty8_Mapping250K_Sty_E04_54090.cel
> > VINOS_p_Sty8_Mapping250K_Sty_E12_54218.cel
> > VINOS_p_Sty8_Mapping250K_Sty_G01_54046.cel
> > VINOS_p_Sty8_Mapping250K_Sty_G12_54222.cel
> > VOLTS_p_Sty9_Mapping250K_Sty_G09_57916.cel
> > VOLTS_p_Sty9_Mapping250K_Sty_H12_57966.cel
> >
> >
> > and the second row looks like:
> >
> > "SNP_A-1780271" 1.8564200401306 1.5095599889755 1.7315399646759
> > 1.530769944191 1.6576000452042 1.474179983139 2.1564099788666
> > 1.775720000267 1.5979499816895 2.1641499996185 1.980849981308
> > 2.180370092392 1.8782299757004 2.1485500335693 1.5325000286102
> > 1.7232999801636 2.2281200885773 1.9381999969482 1.8546999692917
> > 2.1590900421143 2.1928400993347 2.0253200531006
> > 2.6680200099945 2.7435901165009 2.0804998874664 3.2142300605774
> > 2.1001501083374 2.147579908371 3.5244200229645 1.374480009079
> > 1.6613099575043 3.1606800556183 2.0917000770569
> > 1.8727999925613 1.8952000141144 1.813570022583 1.8180899620056
> > 2.2553699016571 1.9273999929428 1.6766400337219 1.3424600362778
> > 1.5666999816895 1.7180800437927 1.9548699855804
> > 1.4444999694824 2.2242999076843 1.7591500282288 2.0480198860168
> > 2.638689994812
> >
> > Thanks a lot!
> >
> > Sincerely,
> >
> > Alex
> >
> >
> > On 6/6/07, jim holtman <[EMAIL PROTECTED]> wrote:
> > >
> > > It would be useful if you could post the first couple of rows of the
> > > data so we can see what it looks like.
> > >
> > > On 6/6/07, ssls sddd <[EMAIL PROTECTED] > wrote:
> > > >
> > > > Dear list,
> > > >
> > > > I need to read a big txt file (around 130Mb; 23800 rows and 49
> > > > columns)
> > > > for downstream clustering analysis.
> > > >
> > > > I first used "Tumor <- read.table("Tumor.txt",header = TRUE,sep =
> > > > "\t")"
> > > > but it took a long time and failed. However, it had no problem if I
> > > > just put
> > > > data of 3 columns.
> > > >
> > > > Is there any way which can load this big file?
> > > >
> > > > Thanks for any suggestions!
> > > >
> > > > Sincerely,
> > > > Alex
> > > >
> > > > [[alternative HTML version deleted]]
> > > >
> > > > ______________________________________________
> > > > R-help@stat.math.ethz.ch mailing list
> > > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > > PLEASE do read the posting guide
> > > > http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> > > > and provide commented, minimal, self-contained, reproducible code.
> > > >
> > >
> > >
> > >
> > > --
> > > Jim Holtman
> > > Cincinnati, OH
> > > +1 513 646 9390
> > >
> > > What is the problem you are trying to solve?
> > >
> >
> >
>
>
> --
> Jim Holtman
> Cincinnati, OH
> +1 513 646 9390
>
> What is the problem you are trying to solve?
>
[[alternative HTML version deleted]]
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and provide commented, minimal, self-contained, reproducible code.
