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Potential confounding issues with data sets #1

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@smithhe2

Training series:
GSE52712: 10/20 samples are amplified from single cells
GSE40987: 2/10 samples are shRNA knockdown of PDEF; 3/10 overexpress PDEF
GSE52262: used only 16/27 samples; only 4 are MCF7 and 4 are MCF10A
GSE12790: used only 20/98 samples; only 1 is MCF7; 18 are MCF10A, of which 6 overexpress HRas and 6 overexpress MEK1
GSE46834: 0/8 samples are MCF7 or MCF10A; 1 each express IRX5, GCNT2, or Foxq1
GSE68651: only 24/36 samples are MCF7 or MCF10A; 18/36 treated with folic acid
GSE74251: only 6/12 samples are MCF7, of which 3 are treated with decitabine
GSE74377: used only 12/16 samples (but all are MCF10A); 8/16 overexpress PHF8; 12/16 are treated with TGFbeta1
Test series:
GSE78011: used only 3/10 samples (but 6/10 are MCF7)
GSE81593: used only 3/12 samples (all are MCF10A, 4 are p53 deletions, 4 overexpress H-Ras, and 4 are p53 deletions overexpressing H-Ras)
GSE75292: 6/6 samples overexpress various miRs
GSE29327: 3/6 samples overexpress miR-221/222
GSE30931: 3/12 samples treated with estrogen, 3/12 with Bortezomib, and 3/12 with both
GSE48398: only 6/36 are MCF10A and 12/36 are MCF7; 18/36 subjected to heat shock
GSE57339: 8/12 overexpress different isoforms of ERBB4 (4 each isoform)
GSE45715: used only 42/53 samples, presumably all the ones labeled 'MCF7'; complex experimental design with overexpression of various genes (BRCA1, BRCA2, PALB2, etc) +/- TNFalpha stimulation

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