In some cases, instead of individual sample records (GSM) containing information regarding sample phenotypes, the GEO Series contains that information in an attached data table. And example is given by GSE3494 where there are two data tables with important information contained within them. Using getGEO with the standard parameters downloads the GSEMatrix file which, unfortunately, does not contain the information in the data tables. This function simply downloads the ``header'' information from the GSE record and parses out the data tables into R data.frames.
getGSEDataTables(GSE)
A list of data.frames.
http://www.ncbi.nlm.nih.gov/geo
dfl = getGSEDataTables("GSE3494")No encoding supplied: defaulting to UTF-8.lapply(dfl,head)#> [[1]] #> INDEX (ID) p53 seq mut status (p53+=mutant; p53-=wt) #> 1 X101B88 p53+ #> 2 X102B06 p53+ #> 3 X104B91 p53+ #> 4 X110B34 p53+ #> 5 X111B51 p53+ #> 6 X127B00 p53+ #> p53 DLDA classifier result (0=wt-like, 1=mt-like) DLDA error (1=yes, 0=no) #> 1 1 0 #> 2 1 0 #> 3 0 1 #> 4 1 0 #> 5 1 0 #> 6 1 0 #> Elston histologic grade ER status PgR status age at diagnosis tumor size (mm) #> 1 G3 ER- PgR- 40 12 #> 2 G3 ER+ PgR+ 51 26 #> 3 G3 ER+ PgR+ 80 24 #> 4 G2 ER+ PgR+ 74 20 #> 5 G3 ER+ PgR+ 41 33 #> 6 G3 ER+ PgR+ 57 22 #> Lymph node status DSS TIME (Disease-Specific Survival Time in years) #> 1 LN- 11.833 #> 2 LN- 11.833 #> 3 LN? 3.583 #> 4 LN- 11.667 #> 5 LN- 7.167 #> 6 LN- 4.667 #> DSS EVENT (Disease-Specific Survival EVENT; 1=death from breast cancer, 0=alive or censored ) #> 1 0 #> 2 0 #> 3 0 #> 4 0 #> 5 1 #> 6 1 #> #> [[2]] #> GEO Sample Accession # Patient ID Affy platform #> 1 GSM79114 X100B08 HG-U133A #> 2 GSM79115 X101B88 HG-U133A #> 3 GSM79116 X102B06 HG-U133A #> 4 GSM79117 X103B41 HG-U133A #> 5 GSM79118 X104B91 HG-U133A #> 6 GSM79119 X105B13 HG-U133A #> #>