getGEO vs GEOmetadb
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Jack Zhu ▴ 170
@jack-zhu-3338
Last seen 6.5 years ago
Hi Thomas, Sorry that I missed your posts on the bioconductor mailing list. We did have issues with updating recent GEO data and that seem has been fixed: ----------------------- > con <- dbConnect(SQLite(), "GEOmetadb.sqlite") > dat <- dbGetQuery(con, "select * from gds where gds = 'GDS4252'") > dat ID gds title 1 3354 GDS4252 Cystic fibrosis bronchial epithelial cells exposure to Pseudomonas aeruginosa PA01 biofilms description 1 Analysis of cystic fibrosis (CF) bronchial epithelial CFBE41o- cells exposed to Pseudomonas aeruginosa PA01 biofilms. Cells overexpressing 508del-CFTR and cells rescued with wild type CFTR were examined. CFTR mutations enhance the inflammatory response in the lung to PA01 infection. type pubmed_id gpl platform_organism platform_technology_type feature_count sample_organism sample_type channel_count 1 Expression profiling by array 22821996 GPL570 Homo sapiens in situ oligonucleotide 54675 Homo sapiens RNA 1 sample_count value_type gse order update_date 1 16 transformed count GSE30439 none 2013-04-23 ---------------------------- Could you redonwload the GEOmetadb.sqlite.gz and try again? Please don't hesitate to contact me directly if you still see any problems. Thanks. Jack On Thu, Jun 13, 2013 at 9:05 AM, Thomas H. Hampton <thomas.h.hampton at="" dartmouth.edu=""> wrote: > Hi Sean and Jack, > > Sorry to pester you with this. I posted it to BioC twice and got no response so I thought I should try contacting you more directly. > > > The following getGEO query retrieves data files and meta data for a recent GEO submission of mine, > one that has been curated: > > GDS4252 <- getGEO("GDS4252") > Columns(GDS4252) >> str(Columns(GDS4252)) > 'data.frame': 16 obs. of 4 variables: > $ sample : Factor w/ 16 levels "GSM754979","GSM754980",..: 5 6 7 8 1 2 3 4 13 14 ... > $ genotype/variation: Factor w/ 2 levels "CFTR mutant",..: 1 1 1 1 1 1 1 1 2 2 ... > $ agent : Factor w/ 2 levels "PA01","unexposed": 1 1 1 1 2 2 2 2 1 1 ... > > The folks at NCBI have correctly created two factors with two levels to describe the 16 samples in my experiment. > > I am interested in retrieving similar information using GEOmetadb, but this has proved problematic. > > getSQLiteFile(destdir = getwd(), destfile = "GEOmetadb.sqlite.gz") > > con <- dbConnect(SQLite(), "GEOmetadb.sqlite") > dat <- dbGetQuery(con, "select * from gds where gds = 'GDS4252'") > >> dat > [1] ID gds title > [4] description type pubmed_id > [7] gpl platform_organism platform_technology_type > [10] feature_count sample_organism sample_type > [13] channel_count sample_count value_type > [16] gse order update_date > <0 rows> (or 0-length row.names) > > It seems, for starters, that this GDS identifier for my particular submission isn't accounted for in the current > database. > > Others are, so it looks like my syntax and so forth is ok: > >> dat <- dbGetQuery(con, "select gds from gds limit 10") >> dat > gds > 1 GDS5 > 2 GDS6 > 3 GDS10 > 4 GDS12 > 5 GDS15 > 6 GDS16 > 7 GDS17 > 8 GDS18 > 9 GDS19 > 10 GDS20 > > > There is also the question of where a set of fields (variable in number) describing sample factors and their levels would actually "live" > in the SQLite database. > > This information does not seem to be an attribute of the GDS in any case: > >> dat <- dbGetQuery(con, "select fieldname from geodb_column_desc where TableName = 'gds'") >> dat > FieldName > 1 ID > 2 channel_count > 3 description > 4 feature_count > 5 gds > 6 order > 7 platform > 8 platform_organism > 9 platform_technology_type > 10 pubmed_id > 11 reference_series > 12 sample_count > 13 sample_organism > 14 sample_type > 15 title > 16 type > 17 update_date > 18 value_type > > Nor does it seem to be a feature stored in the samples: > >> dat <- dbGetQuery(con, "select fieldname from geodb_column_desc where TableName = 'gsm'") >> dat > FieldName > 1 ID > 2 channel_count > 3 characteristics_ch1 > 4 characteristics_ch2 > 5 contact > 6 data_processing > 7 data_row_count > 8 description > 9 extract_protocol_ch1 > 10 extract_protocol_ch2 > 11 gpl > 12 gse > 13 gsm > 14 hyb_protocol > 15 label_ch1 > 16 label_ch2 > 17 label_protocol_ch1 > 18 label_protocol_ch2 > 19 last_update_date > 20 molecule_ch1 > 21 molecule_ch2 > 22 organism_ch1 > 23 organism_ch2 > 24 source_name_ch1 > 25 source_name_ch2 > 26 status > 27 submission_date > 28 supplementary_file > 29 title > 30 treatment_protocol_ch1 > 31 treatment_protocol_ch2 > 32 type > > > Any advice greatly appreciated. > > > Tom >
Lung Homo sapiens Pseudomonas aeruginosa GEOmetadb Lung Homo sapiens Pseudomonas aeruginosa • 1.4k views
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