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PROVIDER: PRJEB53459 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This series includes microarrays from 36 patient samples and 2 cell-culture controls, used to optimize and validate the pathogen detection microarray (Wong, et. al. 2007) Keywords: viral pathogen detection
2007-05-29 | GSE7779 | GEO
Project description:To identify a robust diagnostic biomarker for PDAC, we used FF samples in a meta-analysis with five other publicly available data sets. The identified biomarker genes were subsequently validated in the remaining samples to test the detection performance of FFPE samples.
2018-05-11 | GSE101448 | GEO
Project description:Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter, (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlation of >0.94 and >0.80 with NanoString and ScriptSeq protocols respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively. Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transciptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries but detection of eSNV and fusion transcripts was less sensitive.
2013-12-06 | GSE51124 | GEO
Project description:DNA copy number changes with or without accompanying copy neutral changes such as unparental disomy (UPD) is a feature of the cancer genome that is linked to cancer development. However, technical problems with archived formalin-fixed, paraffin-embedded (FFPE) tissue samples have limited their general use in genomic profiling studies done using high-density single nucleotide polymorphism (SNP) microarray. To overcome the current problems with the use of this material in the detection of DNA copy number and copy neutral changes, we have devised two new protocols for extracting DNA from FFPE tissue. Genotyping efficiency and accuracy were improved using our novel protocols. After censoring the larger fragments, we obtained call rates for FFPE DNA equivalent to those for FF tissue DNA, with concordance rates between FFPE and FF tumor exceeding 99%. Identical DNA copy number changes were obtained for FFPE and FF; and between two new extraction protocols in tumor samples by using Affymetrix® high-density oligo-based SNP microarray platform. We observed UPD and recurrent gains and losses in tumor samples. Interestingly, we also identified UPD in the 5q and 13q regions in matching normal blood, FF adjacent breast tissue and tumor tissue in two samples. In conclusion, our new two DNA extraction protocols should substantially improve the ability to use archived material to help elucidate the complexity of early-stage breast cancer genomes. Keywords: SNP based array
2008-09-18 | GSE9154 | GEO
Project description:Background: As degradation of formalin-fixed paraffin-embedded (FFPE) samples limits ability to expression profile, we explored factors predicting success for FFPE profiling and investigated an approach overcoming this limitation. Methods: Bladder (n=141, stored 3-8 years) and cervix (n=160, stored 8-23 years) carcinoma FFPE samples were hybridised to Affymetrix Exon1.0ST arrays. Percent detection above background (%DABG) measured technical success. Biological signal was assessed by distinguishing cervix squamous cell carcinoma (SCC) and adenocarcinoma (AC) using a gene signature. Precursor mir-205 was measured by Exon array and mature miR-205 by qRT-PCR. Eight-old and -young cervix samples were compared using Affymetrix miRNA 2.0 arrays. For comparison, the 'cervix_tumour_cs1_113' (previsously submitted GSM677307) was included and re-analyzed with the samples from the current study (total 161 Cervix samples). Results: RNA quality controls (e.g. RNA integrity number) failed to predict profiling success, but sample age correlated with %DABG in bladder (R2=-0.30, p<0.01) and cervix (R2=-0.69, p<0.01). Biological signal was lost in older samples and neither a signature nor precursor mir-205 separated samples by histology. miR-205 qRT-PCR discriminated SCC from AC, validated by miRNA profiling (26-fold higher in SCC; p=1.10x10-5). Median miRNA probeset expression of eight-old and eight-young cervix samples correlated well (R2=0.95) overcoming the age-related bias of mRNA probesets, suggesting miR-205 stability generalises across microRNA. Conclusions: microRNA profiling overcomes the limitation of degraded FFPE samples
2012-07-04 | GSE39015 | GEO
Project description:Pathogen detection microarrays analyzing honeybee samples taken after parasitization with a predatory fly, oligos correspond to specific pathogens or pathogen families of viruses, bacteria, fungi, protists, and other parasites Samples were analyzed with the E-Predict analysis package.
2012-08-01 | GSE29749 | GEO
Project description:Viral metagenomics for pathogen detection in CSF and plasma
| PRJEB34029 | ENA
Project description:Pathogen detection microarrays analyzing honeybee samples taken from the same hives over the course of a year, oligos correspond to specific pathogens or pathogen families of viruses, bacteria, fungi, protists, and other parasites Samples were analyzed with the E-Predict analysis package
2011-06-06 | GSE28235 | GEO