87ada597-3afa-4005-b4cf-67819821b42b - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008793 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..
| 2612481 | ecrin-mdr-crc
Project description:Intervention type:DRUG
Name of intervention:Huaier
Dose form / Japanese Medical Device Nomenclature:GRANULES
Route of administration / Site of application:ORAL
Dose per administration:20?
g
Dosing frequency / Frequency of use:OTHER, SPECIFY
20g? per day
Planned duration of intervention:3 months to extending if necessary
Intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary
detailes of teratment arms:hepatocellular carcinoma, breast cancer, colorectal cancer and related gastrointestinal cancers, urologic cancers including prostate cancer, pancreas cancer, and lung cancer, etc.
Comparative intervention name:None
Dose form / Japanese Medical Device Nomenclature:
Route of administration / Site of application:
Dose per administration:
Dosing frequency / Frequency of use:
Planned duration of intervention:
Intended dose regimen:
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.
Study Design: Comparative test, None, No, open(masking not used), EXPLORATORY
| 98681 | ecrin-mdr-crc
Project description:Primary outcome(s): Cancer-related gene alteration, expression of protein, and expression of RNA
| 2645675 | ecrin-mdr-crc
Project description:Cardiac mRNA profiles of 2-month-old wild-type (WT) and muscle Sdhaf4 knockout (Sdhaf4−/−) mice were generated by deep sequencing, in 6 repeats, usingIllumina HiSeqTM. HTSeq v0.9.1 was used to count the reads numbers mapped to each gene. Genes with an adjusted P-value <0.05 found by DESeq were assigned as differentially expressed. Corrected P-value of 0.005 and log2 (Fold change) of 1 were set as the threshold for significantly differential expression.
2022-03-24 | GSE163809 | GEO
Project description:To generate this dataset in RNA-seq, we performed a mixing experiment, in which we mixed mRNAs from three cell lines: lung adenocarcinoma in humans (H1092), cancer-associated fibroblasts (CAFs) and tumor infiltrating lymphocytes (TIL), at different proportions to generate 32 samples, including 9 samples that correspond to three repeats of a pure cell line sample for three cell lines. The RNA amount of each tissue in the mixture samples was calculated on the basis of real RNA concentrations tested in the biologist’s lab. This dataset was generated in house and then used to generate the count table that counts the number of reads mapped to each exon for all the samples. This count data will be pre-processed by total count normalization and genes that contained zero counts are removed.
2018-10-12 | GSE121127 | GEO
Project description:RNA-seq count data at 3 timepoints was generated for Zika-exposed and Zika-naïve individuals in order to assess associated signatures
2019-04-17 | GSE129882 | GEO
Project description:Gene expression for 303 ADME and ADME related genes (averaged log2 signal intensities using Human-WG6v2 Expression BeadChip)
| EGAD00010001709 | EGA
Project description:Comparison between in vitro transcription- and cDNA-mediated annealing, selection and ligation (DASL)-based assays on brain-specific reference RNA, and postmortem frozen and formalin fixed brain tissue from autistic and control cases. Investigation of data preprocessing techniques for DASL-assayed RNA samples from frozen brain tissue. IVT- and DASL-based expression assays were performed on 10 reference RNA samples (brain and pooled artificially degraded at 0, 10, 30, and 60 min), 4 formalin-fixed tissue-extracted RNA samples with replicates, and 57 frozen tissue-extracted RNA samples with replicates. A subset of the 57 (N=33 samples) from frozen brain tissue assayed using the DASL-based platform were then used to test different dataset preprocessing strategies implemented in the lumi package in R/Bioconductor. The data from frozen-tissue extracted DASL-processed RNA samples passing exclusion criteria were log2 transformed and normalized using quantile normalisation with lumi in R (quantile-normalized data available as a supplementary file linked to the Series record).
2012-04-02 | E-GEOD-28475 | biostudies-arrayexpress
Project description:We report the results of performing RNA sequencing using RNA extracted from TC28a2 cells grown in the presence of hypertrophic differentiation medium compared to RNA extracted from TC28a2 cells grown in growth medium. For preparation of samples for RNA sequencing, total RNAs were extracted from TC28a2 cells treated with growth medium (n=2) or hypertrophic medium (n=3) at day 5 of differentiation. RNA was extracted using Trizol (Invitrogen) following the protocols provided by the manufacturer. Isolated RNAs were submitted to the Macrogen Inc. (Macrogen Inc., Seoul, South Korea) for total RNA-sequencing. The overall quality of the extracted total RNAs were validated using spectrophotometry. To remove low quality and adapter sequence, the raw was read by the sequencer before analysis and align the processed reads to the Homo sapiens using HISAT2 v2.1.059. The reference genome sequence of Homo sapiens (hg19) and annotation data were downloaded from the NCBI, and transcript assembly of known transcripts was then processed by StringTie v2.1. Base on the result of that, expression abundance of transcript and gene were calculated as read count or FPKM value (Fragments Per Kilobase of exon per Million fragments mapped) per sample. The expression profiles are used to do additional analysis such as DEG (Differentially Expressed Genes). The relative abundances of gene were measured in read count using StringTie. Genes with one more than zeroed read count values in the samples were excluded. Filtered data were log2-transformed and subjected to RLE Normalization. Statistical significance of the differential expression data was determined using DESeq2 nbinomWaldTest and fold change in which the null hypothesis was that no difference exists among groups. False discovery rate (FDR) was controlled by adjusting p value using Benjamini-Hochberg algorithm. For DEG set, hierarchical clustering analysis was performed using complete linkage and Euclidean distance as a measure of similarity. Enrichment of gene ontology analysis was performed for DEGs using g:Profiler and KEGG pathway analysis was tested based on KEGG pathway (https://www.genome.jp/kegg/) database. We used multidimensional scaling (MDS) method to visualize the similarities among samples. We applied to the Euclidean distance as the measure of the dissimilarity. Hierarchical clustering analysis also was performed using complete linkage and Euclidean distance as a measure of similarity to display the expression patterns of differentially expressed transcripts which are satisfied with fold change ≥2 and raw p <0.05. All data analysis and visualization of differentially expressed genes was conducted using R 3.6.1(www.r-project.org).
2022-04-03 | GSE199847 | GEO
Project description:Purpose: To investigate the global impact of lignin perturbation on transcription in plants, we analyzed transcriptomes from rapidly lignifying stem tissue in wild-type Arabidopsis and 13 selected mutants. Methods: RNA-sequencing was conducted to profile the transcriptome in basal stem tissue of Arabidopsis plants. PolyA+ RNA libraries were constructed and paired-end sequencing was performed on Illumina NovaSeq 6000. The sequence reads that passed quality filters were aligned to the TAIR10 reference genome using HISAT2. Gene counts were analyzed using HTSeq-count program and differential gene expression using DESeq2. Results: The whole dataset contains 20974 expressed genes and 5581 differentially expressed genes in at least one mutant (ANOVA, FDR < 0.05, Fold change ≥ 2 fold).
2022-07-15 | GSE206323 | GEO