Similar Datasets
Project description:This is another test of the quality control text mix. This is not really useful for anybody but me.
2023-08-04 | MSV000092593 | MassIVE
Project description:DNA was isolated from whole red blood cells from various lines and crosses of broiler chickens. DNA was genotyped using Axiom genome-wide chicken array and cel files were analyzed using Axiom Analysis Suite Software (version 3.0.1) with Gallus gallus 5.0 using the software's Best Practices for agricultural animals. The results were exported (Genotyping_Data-3-21-2018.vcf) for all genotype calls and text file of all SNPs with >= 97% call rate rate was also produced for filtering the VCF file (ALL_SNPSs_with_Call_Rate_97_Plus_3-21-2018).
2019-05-25 | GSE131764 | GEO
Project description:Purpose: Build genesets using text mining and validate the geneset with data from public repository and a dataset generated in house using in vitro models and RNA-seq Methods: Mucus hypersecretion and mucociliary dysfucntion adverse outcome pathways (AOPs) genesets were build using the text mining method described by Rani et al., 2015. Validation was performed using RNA expression data from cigarette and e-cigarette aerosol treated cells, IL-13 treated airway cells, and COPD-lung biopsies. The cigarette and e-cigarette aerosol RNA-samples from airway cells were generated and sequenced in house. The other dataset were publically available. Results: Using unsupervised clustering, the mucus hypersecretion and mucociliary dysfunction genesets were able to discriminate the cigartte treated cells from the e-cigarettes and the air control. The e-cigarette and the air control clustered together. Clustering was also observed with IL-13 treated cells. IL-13 is an induced of mucus hypersecretion. Clustering was not observed when COPD RNA-seq samples were used. PCA analysis revealed some degree of grouping based on disease status, but this was also heavily confounded by other parameters. Conclusions: Our study described the first application of text mining to build genesets relevant to AOPs. In vitro validation confirmed the genesets could discriminates between treatment that induce mucus hypersecretion phenotypes, however this could not be confirmed with COPD biopsy samples. This could be due to a series of technical confouding factors and the heterogeneity of the COPD disease.
2020-04-30 | GSE142100 | GEO
Project description:PCOS is a widespread disease that primarily caused in-pregnancy in pregnant-age women. Normoandrogen (NA) and Hyperandrogen (HA) PCOS are distinguished under distinct level of testosterone, while markers and expression patterns for both subtypes were not adequately studied. Text-mining analysis stated the correlation for PCOS with granusola cells and thus we performed microarray analysis on granusola cells from HA PCOS, NA PCOS and normal tissue from individuals, and afterwards downloaded RNA-seq and microarray data from NCBI GEO database on granusola cells from PCOS and normal ovary. Applying our newly developed method using Monte Carlo algorithm and text mining method on combined data, we identified several potential markers for HA and NA PCOS. RT-PCR and Western blotting results validated the expression pattern of these markers for HA and NA PCOS as bioinformatical prediction. Further gene ontology (GO) and text-mining analysis discovered that (1) NA PCOS was highly correlated with estrogen-driven tumors including ovarian, breast and endometrial cancer as compared with normal granusola cells. NA PCOS specific genes IL6R and CD274 were bioinformatically predicted and experimentally validated and thus might be the key factor behind the mechanism responsible for the tumor-like pattern for NA PCOS; (2) HA PCOS showed high correlation with keratinization, epidermis development, GTPase activity, glomerular basement membrane development and apoptosis corresponding to the fact HA PCOS patients express characteristic of hirsutism, diabetes and obesity. Meanwhile HA PCOS was sustantially lowerly related with estrogen-driven tumors as compared with normal granusola cells.
2019-09-19 | GSE137684 | GEO
Project description:Total pancreatic RNA was isolated from 3 week old NOD.scid, NOD, BDC2.5/NOD and BDC2.5/NOD.scid animals by GITC method. Targets were produced using standard Affymetrix procedures from about 10ug total RNA. The data from NOD.scid, NOD, BDC2.5/NOD and BDC2.5/NOD.scid Affymetrix MGU74Av2 cel files was converted into Robust Multi Array (RMA) text file for analysis using GeneSpring 6.1 Keywords: other
2005-01-26 | GSE1623 | GEO
Project description:Your dataset must be tagged with at least one keyword there is
no limit Keywords are custom text so you must click the
button after entering text
| MSV000088146 | GNPS
Project description:Effects of soy isoflavones, genistein and daidzein, on the hepatic gene expression profile and indices for lipid metabolism were compared in rats. The GeneChip data was normalized and summarized by using SuperNORM data service (Skylight Biotech Inc.). Significance of expressional change among groups was tested by 2-way ANOVA on the normalized CEL data, which was deposited in a tab-separated ASCII text format. Principal components were identified on the summarized gene data.
2012-10-10 | GSE41420 | GEO