Hi,

I would like to get information on which samples are cases and which are controls.
I am using the following commands :

#creating GDS list
annotgds = dbGetQuery(con,"select GDS from gds")

#getting data for first 20 GDS
gdslist <- sapply(annotgds[1:20,1],getGEO)

#using column method get the info
gds_col=sapply(gdslist[1:20],function(a) {Columns(a)}

Below is the result for first two GDS:

$GDS10
   sample tissue        strain      disease.state                                     description
1  GSM582 spleen           NOD           diabetic           Value for GSM582: NOD_S1; src: Spleen
2  GSM589 spleen           NOD           diabetic           Value for GSM589: NOD_S2; src: Spleen
3  GSM583 spleen          Idd3 diabetic-resistant          Value for GSM583: Idd3_S1; src: Spleen
4  GSM590 spleen          Idd3 diabetic-resistant          Value for GSM590: Idd3_S2; src: Spleen
5  GSM584 spleen          Idd5 diabetic-resistant          Value for GSM584: Idd5_S1; src: Spleen
6  GSM591 spleen          Idd5 diabetic-resistant          Value for GSM591: Idd5_S2; src: Spleen
7  GSM585 spleen     Idd3+Idd5 diabetic-resistant        Value for GSM585: Idd3+5_S1; src: Spleen
8  GSM592 spleen     Idd3+Idd5 diabetic-resistant        Value for GSM592: Idd3+5_S2; src: Spleen
9  GSM586 spleen          Idd9 diabetic-resistant          Value for GSM586: Idd9_S1; src: Spleen
10 GSM593 spleen          Idd9 diabetic-resistant          Value for GSM593: Idd9_S2; src: Spleen
11 GSM587 spleen      B10.H2g7        nondiabetic      Value for GSM587: B10.H2g7_S1; src: Spleen
12 GSM594 spleen      B10.H2g7        nondiabetic      Value for GSM594: B10.H2g7_S2; src: Spleen
13 GSM588 spleen B10.H2g7 Idd3        nondiabetic Value for GSM588: B10.H2g7 Idd3_S1; src: Spleen
14 GSM595 spleen B10.H2g7 Idd3        nondiabetic Value for GSM595: B10.H2g7 Idd3_S2; src: Spleen
15 GSM596 thymus           NOD           diabetic           Value for GSM596: NOD_T1; src: Thymus
16 GSM603 thymus           NOD           diabetic           Value for GSM603: NOD_T2; src: Thymus
17 GSM597 thymus          Idd3 diabetic-resistant          Value for GSM597: Idd3_T1; src: Thymus
18 GSM604 thymus          Idd3 diabetic-resistant          Value for GSM604: Idd3_T2; src: Thymus
19 GSM598 thymus          Idd5 diabetic-resistant          Value for GSM598: Idd5_T1; src: Thymus
20 GSM605 thymus          Idd5 diabetic-resistant          Value for GSM605: Idd5_T2; src: Thymus
21 GSM599 thymus     Idd3+Idd5 diabetic-resistant        Value for GSM599: Idd3+5_T1; src: Thymus
22 GSM606 thymus     Idd3+Idd5 diabetic-resistant        Value for GSM606: Idd3+5_T2; src: Thymus
23 GSM600 thymus          Idd9 diabetic-resistant          Value for GSM600: Idd9_T1; src: Thymus
24 GSM607 thymus          Idd9 diabetic-resistant          Value for GSM607: Idd9_T2; src: Thymus
25 GSM601 thymus      B10.H2g7        nondiabetic      Value for GSM601: B10.H2g7_T1; src: Thymus
26 GSM608 thymus      B10.H2g7        nondiabetic      Value for GSM608: B10.H2g7_T2; src: Thymus
27 GSM602 thymus B10.H2g7 Idd3        nondiabetic Value for GSM602: B10.H2g7 Idd3_T1; src: Thymus
28 GSM609 thymus B10.H2g7 Idd3        nondiabetic Value for GSM609: B10.H2g7 Idd3_T2; src: Thymus

$GDS100
  sample       protocol      time
1 GSM549 not irradiated  0 minute
2 GSM542 not irradiated 20 minute
3 GSM543 not irradiated 60 minute
4 GSM547     irradiated  5 minute
5 GSM544     irradiated 10 minute
6 GSM545     irradiated 20 minute
7 GSM546     irradiated 40 minute
8 GSM548     irradiated 60 minute


The columns are different in each GDS,so I am not able to get that information and combine it.



ii) The other technique I used is the expression set.The commands for this are:

eset_list <- sapply(gdslist[1:3],GDS2eSet,do.log2=TRUE)

eset_col=sapply(eset_list[1:3],function(a) {pData(a)}

$GDS10
       sample tissue        strain      disease.state                                     description
GSM582 GSM582 spleen           NOD           diabetic           Value for GSM582: NOD_S1; src: Spleen
GSM589 GSM589 spleen           NOD           diabetic           Value for GSM589: NOD_S2; src: Spleen
GSM583 GSM583 spleen          Idd3 diabetic-resistant          Value for GSM583: Idd3_S1; src: Spleen
GSM590 GSM590 spleen          Idd3 diabetic-resistant          Value for GSM590: Idd3_S2; src: Spleen
GSM584 GSM584 spleen          Idd5 diabetic-resistant          Value for GSM584: Idd5_S1; src: Spleen
GSM591 GSM591 spleen          Idd5 diabetic-resistant          Value for GSM591: Idd5_S2; src: Spleen
GSM585 GSM585 spleen     Idd3+Idd5 diabetic-resistant        Value for GSM585: Idd3+5_S1; src: Spleen
GSM592 GSM592 spleen     Idd3+Idd5 diabetic-resistant        Value for GSM592: Idd3+5_S2; src: Spleen
GSM586 GSM586 spleen          Idd9 diabetic-resistant          Value for GSM586: Idd9_S1; src: Spleen
GSM593 GSM593 spleen          Idd9 diabetic-resistant          Value for GSM593: Idd9_S2; src: Spleen
GSM587 GSM587 spleen      B10.H2g7        nondiabetic      Value for GSM587: B10.H2g7_S1; src: Spleen
GSM594 GSM594 spleen      B10.H2g7        nondiabetic      Value for GSM594: B10.H2g7_S2; src: Spleen
GSM588 GSM588 spleen B10.H2g7 Idd3        nondiabetic Value for GSM588: B10.H2g7 Idd3_S1; src: Spleen
GSM595 GSM595 spleen B10.H2g7 Idd3        nondiabetic Value for GSM595: B10.H2g7 Idd3_S2; src: Spleen
GSM596 GSM596 thymus           NOD           diabetic           Value for GSM596: NOD_T1; src: Thymus
GSM603 GSM603 thymus           NOD           diabetic           Value for GSM603: NOD_T2; src: Thymus
GSM597 GSM597 thymus          Idd3 diabetic-resistant          Value for GSM597: Idd3_T1; src: Thymus
GSM604 GSM604 thymus          Idd3 diabetic-resistant          Value for GSM604: Idd3_T2; src: Thymus
GSM598 GSM598 thymus          Idd5 diabetic-resistant          Value for GSM598: Idd5_T1; src: Thymus
GSM605 GSM605 thymus          Idd5 diabetic-resistant          Value for GSM605: Idd5_T2; src: Thymus
GSM599 GSM599 thymus     Idd3+Idd5 diabetic-resistant        Value for GSM599: Idd3+5_T1; src: Thymus
GSM606 GSM606 thymus     Idd3+Idd5 diabetic-resistant        Value for GSM606: Idd3+5_T2; src: Thymus
GSM600 GSM600 thymus          Idd9 diabetic-resistant          Value for GSM600: Idd9_T1; src: Thymus
GSM607 GSM607 thymus          Idd9 diabetic-resistant          Value for GSM607: Idd9_T2; src: Thymus
GSM601 GSM601 thymus      B10.H2g7        nondiabetic      Value for GSM601: B10.H2g7_T1; src: Thymus
GSM608 GSM608 thymus      B10.H2g7        nondiabetic      Value for GSM608: B10.H2g7_T2; src: Thymus
GSM602 GSM602 thymus B10.H2g7 Idd3        nondiabetic Value for GSM602: B10.H2g7 Idd3_T1; src: Thymus
GSM609 GSM609 thymus B10.H2g7 Idd3        nondiabetic Value for GSM609: B10.H2g7 Idd3_T2; src: Thymus

$GDS100
       sample       protocol      time
GSM549 GSM549 not irradiated  0 minute
GSM542 GSM542 not irradiated 20 minute
GSM543 GSM543 not irradiated 60 minute
GSM547 GSM547     irradiated  5 minute
GSM544 GSM544     irradiated 10 minute
GSM545 GSM545     irradiated 20 minute
GSM546 GSM546     irradiated 40 minute
GSM548 GSM548     irradiated 60 minute


here, also the results are same and I am not able to extract the information I need due to difference in column names.
Can anyone help on this?

From my another post,

https://stat.ethz.ch/pipermail/bioconductor/2013-December/056361.html



 I need Gene information as well but when I am looking over my gplllist object
annotgpl = dbGetquery(con,"select distinct GPL from gds")
gpllist <- sapply(annotgpl[1:438,1],getGEO,AnnotGPL=TRUE)
genes_new<- unlist(sapply(gpllist[1:3], function(a) {Table(a)[,'Gene ID']}))
This is the result of first 3 gene id's in first gpl object(GPL13) using the command above. "1""GPL13"
"13""GPL13"
"26""GPL13" However, I am getting altogether different gene ids's while doing it for all 3 gpl objects together as seen above.If I am doing it separately, then only i am getting the gene id's which are the correct ones, that I notice in gpllist object.
The count of genes in each case (doing together vs separate )remain same . ii.) genes_new<- unlist(sapply(gpllist[1], function(a) {Table(a)[,'Gene ID']})) "818888" "GPL13"
"821523" "GPL13"
"824405" "GPL13"
I will really appreciate any help in this.
Thanks in advance,

Rohan

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