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Correlation between BCR batch and the processing batch for 27k arrays in COAD (January 20, 2012)
| Wiki Markup |
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{csv}Batch on the download page,TCGA Archive code Level 1 from sdrf file,Comment for TCGA Arcive code from sdrf file,"# after ""HumanMethylation27k"" in the file name, Level 1",Batch as the sixth field in the patient barcode,Comments
Batch 28,1.1.0,,1,"0820, 1552, 1551",
Batch 29,2.2.0,,2,"0825, 1551",
Batch 30,3.0.0,,3,A004,
Batch 33,4.0.0,,4,A00B,
Batch 36,5.2.0,1110 is not there probably because sdrf file I have is for the tumor samples only,"5, 7","1110, 0904","all 0904 have 5, 1110 (one sample) is 7"
Batch 41,6.0.0,1110 is not there probably because sdrf file I have is for the tumor samples only,"6,7","1020, 1110","all 1020 have 6, 1110 (one sample) is 7"
Batch 45,7.0.0,,7,1110,
Batch 66,8.0.0,,8,A081,
Batch 76,,,no data,,
Batch 89,,,no data,,
Batch 116,,,no data,,
Batch 123,,,no data,,
Batch 132,,,no data,,
Batch 138,,,no data,,
Batch 154,,,no data,,
Batch 157,,,no data,,
Batch 172 ,,,no data,,{csv} |
Correlation between BCR batch and the processing batch for 27k arrays in READ (January 20, 2012):
| Wiki Markup |
|---|
{csv}Batch on the download page,"# after ""HumanMethylation27k"" in the file name, Level 1",Batch as the sixth field in the patient barcode,Comments
Batch 42,"1, 2, 5, 6","0820, 1552, 0825, 0904, 1116",1 corresponds to 0820 and 1552; 2 corresponds to 0825; 1 sample that corresponds to 5 is 0904; 1 samples that corresponds to 6 is 1116
Batch 43,"3, 4","A004, A00B","A004 corresponds to 3, A00B corresponds to 4"
Batch 46,6,1116,
Batch 67,4,A00B,only one sample is available
Batch 102,no data,,
Batch 122,no data,,
Batch 133,no data,,
Batch 139,no data,,
Batch 158,no data,,{csv} |
Batch vs clinical traits, data collection
Correlation of batch with clinical traits (READ: can be found here, COAD: can be found here). READ, number of batches: 11, COAD, number of batches: 15
Additional technical variables to be considered in normalization: batch (6th field in the patient's barcode), center (2nd field in the patients' barcode), amount, barcode bottom (?), concentration, day, month, year (to be concatenated and considered as a single variable), plate row, plate column. This information is available from clinical_aliquot_public_CANCERTYPE.txt files.
DNA methylation: 27k, level1 downloaded on December 19th, 2011.
Total number of COAD patients (tumor/matched normal/unmatched normal) = 212
Total number of READ patients (tumor/matched normal/unmatched normal) = 81
Place them in the same directory and combine in a single matrix of M values (log2(methylated/unmethylated))
Total number of tumor samples: 237
Extracted batch and center information, relationship between them:
| Code Block |
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> table(center,batch)
batch
center 0820 0825 0904 1020 1110 1116 A004 A00B A081
A6 4 2 0 4 0 0 0 0 0
AA 26 5 31 44 4 0 15 17 13
AF 4 0 0 0 0 1 0 0 0
AG 12 10 8 0 0 17 9 9 0
AY 0 0 0 0 2 0 0 0 0
|
For the combined DNA methylation dataset (237 patients) batch vs clinical traits significant correlations (P value = 0.05) are listed. Note: traits 1 and 2 should be used for the calculation of the survival and then Cox model should be used to show that batch is predictive of survival. Complete list can be found here
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Correlation between BCR batch and the processing batch for 27k arrays in READ (January 20, 2012):
Batch vs clinical traits, data collection
Correlation of batch with clinical traits (READ: can be found here, COAD: can be found here). READ, number of batches: 11, COAD, number of batches: 15
Additional technical variables to be considered in normalization: batch (6th field in the patient's barcode), center (2nd field in the patients' barcode), amount, barcode bottom (?), concentration, day, month, year (to be concatenated and considered as a single variable), plate row, plate column. This information is available from clinical_aliquot_public_CANCERTYPE.txt files.
DNA methylation: 27k, level1 downloaded on December 19th, 2011.
Total number of COAD patients (tumor/matched normal/unmatched normal) = 212
Total number of READ patients (tumor/matched normal/unmatched normal) = 81
Place them in the same directory and combine in a single matrix of M values (log2(methylated/unmethylated))
Total number of tumor samples: 237
Extracted batch and center information, relationship between them:
| Code Block |
|---|
> table(center,batch)
batch
center 0820 0825 0904 1020 1110 1116 A004 A00B A081
A6 4 2 0 4 0 0 0 0 0
AA 26 5 31 44 4 0 15 17 13
AF 4 0 0 0 0 1 0 0 0
AG 12 10 8 0 0 17 9 9 0
AY 0 0 0 0 2 0 0 0 0
|
For the combined DNA methylation dataset (237 patients) batch vs clinical traits significant correlations (P value = 0.05) are listed. Note: traits 1 and 2 should be used for the calculation of the survival and then Cox model should be used to show that batch is predictive of survival. Complete list can be found here
Correlation with survival
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