Description Usage Arguments Value Author(s) References See Also Examples
Indentify diiffentially expressed genes using rank product method
1 2 |
x |
the value returned by function RP, RPadvance, RSadvance, RankProducts or RP.advance |
cutoff |
The pfp threshold value used to select genes |
method |
if cutoff is provided, the method needs to be selected to identify genes. "pfp" uses percentage of false prediction, which is a default setting. "pval" uses p-values which is less stringent than pfp |
logged |
if "TRUE", data has been logged, otherwise set it to "FALSE" |
logbase |
base used when taking log, used to restore the fold change.The default value is 2, this will be ignored if logged=FALSE |
gene.names |
if "NULL", no gene name will be attached to the output table |
num.gene |
number of candidates genes of interests, if cutoff is provided, this will be ignored |
Two tables of identified genes with gene.index: index of gene in the original data set RP/Rsum: Computed rank product/sum for each gene FC:(class1/class2): Expression Fold change of class 1/ class 2. pfp: estimated pfp for each gene if the gene is used as cutoff point P.value: estimated p-value for each gene Table 1 list genes that are up-regulated under class 2, Table 1 ist genes that are down-regulated under class 2
Fangxin Hong fhong@salk.edu
Breitling, R., Armengaud, P., Amtmann, A., and Herzyk, P.(2004) Rank Products: A simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments, FEBS Letter, 57383-92
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | # Load the data of Golub et al. (1999). data(golub)
# contains a 3051x38 gene expression
# matrix called golub, a vector of length called golub.cl
# that consists of the 38 class labels,
# and a matrix called golub.gnames whose third column
# contains the gene names.
data(golub)
#use a subset of data as example, apply the rank
#product method
subset <- c(1:4,28:30)
#Setting rand=123, to make the results reproducible,
#identify genes
RP.out <- RP(golub[,subset],golub.cl[subset],rand=123)
#get two lists of differentially expressed genes
#by setting FDR (false discivery rate) =0.05
table=topGene(RP.out,cutoff=0.05,method="pfp",logged=TRUE,logbase=2,
gene.names=golub.gnames[,3])
table$Table1
table$Table2
#using pvalue<0.05
topGene(RP.out,cutoff=0.05,method="pval",logged=TRUE,logbase=2,
gene.names=golub.gnames[,3])
#by selecting top 10 genes
topGene(RP.out,num.gene=10,gene.names=golub.gnames[,3])
|
Loading required package: Rmpfr
Loading required package: gmp
Attaching package: 'gmp'
The following objects are masked from 'package:base':
%*%, apply, crossprod, matrix, tcrossprod
C code of R package 'Rmpfr': GMP using 64 bits per limb
Attaching package: 'Rmpfr'
The following objects are masked from 'package:stats':
dbinom, dnorm, dpois, pnorm
The following objects are masked from 'package:base':
cbind, pmax, pmin, rbind
Rank Product analysis for unpaired case
done Table1: Genes called significant under class1 < class2
Table2: Genes called significant under class1 > class2
gene.index RP/Rsum FC:(class1/class2) pfp P.value
HG2724-HT2820_at 418 8.143 0.2689 0.05659 0.0001132
D87116_at 346 8.320 0.2605 0.03057 0.0001223
HG3494-HT3688_at 436 8.653 0.2369 0.02345 0.0001407
gene.index RP/Rsum FC:(class1/class2) pfp P.value
AFFX-HUMRGE/M10098_3_at 6 6.768 4.314 0.02786 5.573e-05
AFFX-HUMRGE/M10098_M_at 5 9.967 3.849 0.05780 2.312e-04
AFFX-HUMRGE/M10098_5_at 4 10.780 4.034 0.05054 3.032e-04
AFFX-M27830_5_at 14 10.800 3.252 0.03811 3.049e-04
Table1: Genes called significant under class1 < class2
Table2: Genes called significant under class1 > class2
$Table1
gene.index RP/Rsum FC:(class1/class2) pfp
HG2724-HT2820_at 418 8.143 0.2689 0.05659
D87116_at 346 8.320 0.2605 0.03057
HG3494-HT3688_at 436 8.653 0.2369 0.02345
D88422_at 378 12.810 0.2684 0.06752
HG987-HT987_at 475 13.740 0.3031 0.06802
D87433_at 350 18.810 0.3543 0.15400
D26579_at 141 28.470 0.3970 0.45540
D10495_at 68 29.680 0.4748 0.44870
D26308_at 140 32.940 0.5013 0.53580
D30755_at 160 33.830 0.5308 0.51940
J03909_at 496 34.260 0.4730 0.48920
D50663_at 219 35.980 0.5953 0.51340
AFFX-HUMTFRR/M11507_3_at 13 37.430 0.5117 0.52780
D50915_at 229 38.430 0.6938 0.52660
D89052_at 381 39.490 0.4630 0.52890
HG620-HT620_at 470 42.080 0.5305 0.58710
D29643_at 155 43.170 0.5360 0.59130
AFFX-HUMTFRR/M11507_M_at 12 45.720 0.5309 0.64830
D00726_at 62 45.790 0.5530 0.61680
D83735_at 303 49.060 0.6354 0.69860
D26129_at 139 51.670 0.5489 0.75770
D79996_at 280 52.420 0.6162 0.74960
HG2788-HT2896_at 419 53.730 0.5948 0.76190
D14874_at 108 53.760 0.5693 0.73110
HG4662-HT5075_at 466 55.400 0.5835 0.75500
HG3286-HT3463_at 431 56.220 0.5563 0.75200
D87937_at 374 56.960 0.6749 0.74710
D00761_at 64 57.480 0.6040 0.73630
HG2810-HT2921_at 420 58.280 0.6070 0.73460
J03040_at 483 59.410 0.6112 0.74290
D10202_at 67 59.550 0.5783 0.72300
D86973_at 333 60.320 0.8143 0.72170
D49817_at 215 60.620 0.5280 0.70810
AF010193_at 52 60.850 0.6096 0.69310
P.value
HG2724-HT2820_at 0.0001132
D87116_at 0.0001223
HG3494-HT3688_at 0.0001407
D88422_at 0.0005401
HG987-HT987_at 0.0006802
D87433_at 0.0018470
D26579_at 0.0063750
D10495_at 0.0071790
D26308_at 0.0096450
D30755_at 0.0103900
J03909_at 0.0107600
D50663_at 0.0123200
AFFX-HUMTFRR/M11507_3_at 0.0137200
D50915_at 0.0147400
D89052_at 0.0158700
HG620-HT620_at 0.0187900
D29643_at 0.0201100
AFFX-HUMTFRR/M11507_M_at 0.0233400
D00726_at 0.0234400
D83735_at 0.0279400
D26129_at 0.0318200
D79996_at 0.0329800
HG2788-HT2896_at 0.0350500
D14874_at 0.0350900
HG4662-HT5075_at 0.0377500
HG3286-HT3463_at 0.0391000
D87937_at 0.0403500
D00761_at 0.0412300
HG2810-HT2921_at 0.0426000
J03040_at 0.0445800
D10202_at 0.0448300
D86973_at 0.0461900
D49817_at 0.0467300
AF010193_at 0.0471300
$Table2
gene.index RP/Rsum FC:(class1/class2) pfp P.value
AFFX-HUMRGE/M10098_3_at 6 6.768 4.314 0.02786 5.573e-05
AFFX-HUMRGE/M10098_M_at 5 9.967 3.849 0.05780 2.312e-04
AFFX-HUMRGE/M10098_5_at 4 10.780 4.034 0.05054 3.032e-04
AFFX-M27830_5_at 14 10.800 3.252 0.03811 3.049e-04
D88270_at 377 12.630 3.535 0.05163 5.163e-04
D11086_at 74 25.340 2.362 0.37840 4.541e-03
D50918_at 232 28.680 2.485 0.46510 6.511e-03
HG1078-HT1078_at 389 29.320 2.255 0.43330 6.933e-03
D83776_at 304 36.770 2.114 0.72640 1.308e-02
HG4036-HT4306_at 451 36.840 2.104 0.65690 1.314e-02
D86479_at 323 38.990 2.083 0.69680 1.533e-02
D86983_at 337 39.860 1.952 0.67780 1.627e-02
D87465_at 369 42.420 1.829 0.73840 1.920e-02
D83780_at 306 43.320 1.987 0.72460 2.029e-02
D42053_at 193 45.720 1.926 0.77800 2.334e-02
D30742_at 159 48.730 2.061 0.85860 2.748e-02
AFFX-HSAC07/X00351_3_st 17 50.590 1.981 0.88800 3.019e-02
D78012_at 267 51.560 1.800 0.87950 3.166e-02
D83785_at 309 54.710 1.610 0.96390 3.663e-02
HG1612-HT1612_at 394 54.850 1.853 0.92110 3.685e-02
D86970_at 330 55.590 1.897 0.90630 3.807e-02
D63880_at 259 56.580 1.753 0.90250 3.971e-02
D63486_at 248 56.750 1.891 0.86960 4.000e-02
J03600_at 491 57.810 1.610 0.87090 4.180e-02
D86967_at 329 57.900 2.127 0.83930 4.196e-02
D87076_at 344 59.890 2.068 0.87360 4.543e-02
D83783_at 307 60.980 1.714 0.87720 4.737e-02
HG3039-HT3200_at 425 61.820 1.724 0.87300 4.889e-02
Table1: Genes called significant under class1 < class2
Table2: Genes called significant under class1 > class2
$Table1
gene.index RP/Rsum FC:(class1/class2) pfp P.value
HG2724-HT2820_at 418 8.143 0.2689 0.05659 0.0001132
D87116_at 346 8.320 0.2605 0.03057 0.0001223
HG3494-HT3688_at 436 8.653 0.2369 0.02345 0.0001407
D88422_at 378 12.810 0.2684 0.06752 0.0005401
HG987-HT987_at 475 13.740 0.3031 0.06802 0.0006802
D87433_at 350 18.810 0.3543 0.15400 0.0018470
D26579_at 141 28.470 0.3970 0.45540 0.0063750
D10495_at 68 29.680 0.4748 0.44870 0.0071790
D26308_at 140 32.940 0.5013 0.53580 0.0096450
D30755_at 160 33.830 0.5308 0.51940 0.0103900
$Table2
gene.index RP/Rsum FC:(class1/class2) pfp P.value
AFFX-HUMRGE/M10098_3_at 6 6.768 4.314 0.02786 5.573e-05
AFFX-HUMRGE/M10098_M_at 5 9.967 3.849 0.05780 2.312e-04
AFFX-HUMRGE/M10098_5_at 4 10.780 4.034 0.05054 3.032e-04
AFFX-M27830_5_at 14 10.800 3.252 0.03811 3.049e-04
D88270_at 377 12.630 3.535 0.05163 5.163e-04
D11086_at 74 25.340 2.362 0.37840 4.541e-03
D50918_at 232 28.680 2.485 0.46510 6.511e-03
HG1078-HT1078_at 389 29.320 2.255 0.43330 6.933e-03
D83776_at 304 36.770 2.114 0.72640 1.308e-02
HG4036-HT4306_at 451 36.840 2.104 0.65690 1.314e-02
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