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How to: Extract probeset summaries (chip effects) as a data frame

Chip effects can be read as a data frame by calling:

data <- extractDataFrame(ces, addNames=TRUE);

The first column is always the units, and the last columns are always the arrays.

Note that this will load all data requested into memory. 

Example: HG-U133_Plus_2

ces <- getChipEffectSet(plm);
print(ces);

ChipEffectSet:
Name: Affymetrix-HeartBrain
Tags: RBC,QN,RMA
Path: plmData/Affymetrix-HeartBrain,RBC,QN,RMA/HG-U133_Plus_2
Platform: Affymetrix
Chip type: HG-U133_Plus_2,monocell
Number of arrays: 3
Names: heart_A, heart_B, heart_C
Time period: 2009-08-12 22:21:59 -- 2009-08-12 22:21:59
Total file size: 1.73MB
RAM: 0.01MB
Parameters: (probeModel: chr "pm")

data <- extractDataFrame(ces, units=1401:1406, addNames=TRUE);
print(data);

     unitName groupName unit group cell    heart_A    heart_B    heart_C
1 201811_x_at           1401     1 1401   50.35944   50.97249   44.04873
2 201812_s_at           1402     1 1402 1247.74109 1182.60449 1151.22278
3 201813_s_at           1403     1 1403   83.30342   81.10368   69.86592
4   201814_at           1404     1 1404   56.92453   65.28267   54.34821
5 201815_s_at           1405     1 1405   23.72381   31.87461   27.95008
6 201816_s_at           1406     1 1406  343.54056  326.27948  272.80453

Example: HuEx-1_0-st-v2

Illustration: Different number of exons (groups/probesets) per gene (unit).

ces <- getChipEffectSet(plm);
print(ces);

ExonChipEffectSet:
Name: Affymetrix-HeartBrain
Tags: RBC,QN,RMA
Path: plmData/Affymetrix-HeartBrain,RBC,QN,RMA/HuEx-1_0-st-v2
Platform: Affymetrix
Chip type: HuEx-1_0-st-v2,coreR3,A20071112,EP,monocell
Number of arrays: 3
Names: cerebellum_A, cerebellum_B, cerebellum_C
Time period: 2009-10-05 23:54:34 -- 2009-10-05 23:54:34
Total file size: 8.15MB
RAM: 0.01MB
Parameters: (probeModel: chr "pm", mergeGroups: logi FALSE)

data <- extractDataFrame(ces, units=101:103, addNames=TRUE);
print(data);

   unitName groupName unit group cell cerebellum_A cerebellum_B cerebellum_C
1   2323743   2323744  101     1 1679       4.9773       3.2216       4.6035
2   2323743   2323745  101     2 1680      28.0082      33.4840      24.9815
3   2323743   2323746  101     3 1681      81.8853      84.7152      90.6801
4   2323743   2323747  101     4 1682      59.3300      78.0417     101.1745
5   2323743   2323748  101     5 1683      11.2939      26.5029      22.1576
6   2323743   2323749  101     6 1684      23.0034      20.3482      19.2598
7   2323774   2323775  102     1 1685       9.7513       8.6798       8.3373
8   2323774   2323776  102     2 1686     126.7435     169.5813     157.2981
9   2323774   2323777  102     3 1687      76.9862     111.4743      79.5220
10  2323774   2323778  102     4 1688      75.9090      77.9127      56.6610
11  2323774   2323779  102     5 1689      39.8756      52.8681      47.4996
12  2323774   2323780  102     6 1690      21.5192      38.1660      36.6005
13  2323774   2323781  102     7 1691      69.1406      83.8591      97.5679
14  2323774   2323782  102     8 1692      68.3016      83.6700      80.9289
15  2323774   2323783  102     9 1693       3.0645       8.2662       8.9555
16  2323790   2323791  103     1 1694       8.0941      10.9351      10.2943
17  2323790   2323792  103     2 1695      45.5133      59.4548      85.2261
18  2323790   2323793  103     3 1696      13.2537      24.0905      11.6845
19  2323790   2323798  103     4 1697      12.4343      15.8386      12.4253
20  2323790   2323799  103     5 1698       6.8943       7.3441       5.2567

Example: GenomeWideSNP_6

Illustration: Each SNP (unit) has (thetaA, thetaB) groups and each CN probe (unit) has only a theta group.

ces <- getChipEffectSet(plm);
print(ces);

CnChipEffectSet:
Name: HapMap270
Tags: 6.0,CEU,testSet,ACC,ra,-XY,BPN,-XY,AVG
Path: plmData/HapMap270,6.0,CEU,testSet,ACC,ra,-XY,BPN,-XY,AVG/GenomeWideSNP_6
Platform: Affymetrix
Chip type: GenomeWideSNP_6,Full,monocell
Number of arrays: 3
Names: NA06985, NA06991, NA06993
Time period: 2009-10-17 00:49:05 -- 2009-10-17 00:49:05
Total file size: 80.85MB
RAM: 0.01MB
Parameters: (probeModel: chr "pm", mergeStrands: logi TRUE, combineAlleles: logi FALSE)

data <- extractDataFrame(ces, units=c(2101:2104,935590:935594), addNames=TRUE);
print(data);

        unitName groupName   unit group    cell  NA06985  NA06991  NA06993
1  SNP_A-2228193         A   2101     1    3580  4518.85  4922.25  5225.94
2  SNP_A-2228193         T   2101     2    3581   522.05   522.58   725.81
3  SNP_A-4234307         A   2102     1    3582  9581.92  5727.58  1274.12
4  SNP_A-4234307         G   2102     2    3583   503.43  2966.96  6061.83
5  SNP_A-2229035         C   2103     1    3584   420.19  4732.66  8462.53
6  SNP_A-2229035         T   2103     2    3585  7162.17  4731.73   207.93
7  SNP_A-2229692         A   2104     1    3586   768.96  1477.57  1134.00
8  SNP_A-2229692         G   2104     2    3587  1117.02   358.71   419.36
9      CN_477984           935590     1 1876054  8724.15  7612.26  8564.70
10     CN_473963           935591     1 1876055  7947.55  5970.75  6425.55
11     CN_473964           935592     1 1876056 12863.29 12642.58 12712.78
12     CN_473965           935593     1 1876057 14373.10 11287.04 10031.57
13     CN_497981           935594     1 1876058 23424.00 26139.35 17312.84