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:RNA-seq expression data from 6 libraries in Caligus rogercresseyi RNA from pooled samples from farmed Atlantic salmon was extracted by mixer-mill (Retsch) homogenization in Trizol (Invitrogen), followed by column clean-up using the RNeasy kit (QIAGEN)
2014-04-12 | E-GEOD-56725 | biostudies-arrayexpress
Project description:Data analysis is a critical part of quantitative proteomics studies in interpreting biological questions. Numerous computational tools including protein quantification, imputation, and differential expression (DE) analysis were generated in the past decade. However, searching optimized tools is still an unsolved issue. Moreover, due to the rapid development of RNA-Seq technology, a vast number of DE analysis methods are created. Applying these newly developed RNA-Seq-oriented tools to proteomics data is still a question that needs to be addressed. In order to benchmark these analysis methods, a proteomics dataset constituted the proteins derived from human, yeast, and drosophila with different ratios were generated. Based on this dataset, DE analysis tools (including array-based and RNA-Seq based), imputation algorithms, and protein quantification methods were compared and benchmarked. This study provided useful information on analyzing quantitative proteomics datasets. All the methods used in this study were integrated into Perseus which are available at https://www.maxquant.org/perseus.
2022-11-16 | PXD029891 | JPOST Repository
Project description:The velvet antler is a unique model for cancer and regeneration research due to its periodic re-generation and rapid growth. Antler growth is mainly triggered by the growth center located in its tip, which consists of velvet skin, mesenchyme and cartilage. Among them, cartilage accounts for most of the growth center. We performed an integrative analysis of the antler cartilage tran-scriptome and proteome at different antler growth stages. RNA-seq results revealed 24,778 uni-genes, 19,243 known protein-coding genes, and 5,535 new predicted genes. Of these, 2,722 were detected with differential expression patterns among 30 d, 60 d, and 90 d libraries, and 488 dif-ferentially expressed genes (DEGs) were screened at 30 d vs. 60 d and 60 d vs. 90 d but not at 30 d vs. 90 d. Proteomic data identified 1,361 known proteins and 179 predicted novel proteins. Compar-ative analyses showed 382 differentially expressed proteins (DEPs), of which 16 had differential expression levels at 30 d vs. 60 d and 60 d vs. 90 d but not at 30 d vs. 90 d. An integrated analysis conducted for DEGs and DEPs showed that gene13546 and its coding protein protein13546 anno-tated in the Wnt signaling pathway may possess important bio-logical functions in rapid antler growth. This study provides in-depth characterization of candidate genes and proteins, providing further insights into the molecular mechanisms controlling antler development.
2022-05-20 | PXD032668 | Pride
Project description:In this study, we make used of mRNA-seq and its ability to reliably quantify isoforms, integrating this data with ribosome profiling and LC-MS/MS, to assign ribosome footprints and peptides at the isoform level. We leverage the principle that most cell types, and even tissues, predominantly express a single principal isoform to set isoform-level mRNA-seq quantifications as priors to guide and improve allocation of footprints or peptides to isoforms. Through tightly integrated mRNAseq, ribosome footprinting and/or LC-MS/MS proteomics we demonstrate that a principal isoform can be identified in over 80% of gene products in homogenous HEK293 cell culture and over 70% of proteins detected in complex human brain tissue. Defining isoforms in experiments with matched RNA-seq and translatomic/proteomic data increases the functional relevance of such datasets and will further broaden our understanding of multi-level control of gene expression. In this PRIDE submission you will find the raw files for the HEK293 cell proteomics. Files for the human brain proteomics can be found at PXD005445. We have also uploaded a zip file that contains the input files for our HEK293 cell analysis, and the isoform level output files – there is a separate folder within the zip files for these. The data used to create the manuscript figures is in the Rdata file. Code for assigning peptides and footprints to isoforms can be found on Github here: https://github.com/rkitchen/EMpire
2018-08-21 | PXD008693 | Pride
Project description:Adult parotid gland RNA-seq libraries, and embryonic submandibular gland RNA-seq libraries
| PRJNA398681 | ENA
Project description:<p>Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12Ac ChIP-seq data for wild-type and mip6delta strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress.</p>
2020-02-14 | MTBLS1320 | MetaboLights
Project description:Epithelial cells and differentiated fiber cells represent distinct compartments in the ocular lens. While previous studies have revealed proteins that are preferentially expressed in epithelial vs. fiber cells, a comprehensive proteomics library comparing the molecular composition of epithelial vs. fiber cells is essential for understanding lens formation, function, disease and regenerative potential, and for efficient differentiation of pluripotent stem cells for modeling of lens development and pathology in vitro. To compare protein composition between the lens epithelium and fibers, we employed tandem mass spectrometry (2DLC/ MS) analysis of micro-dissected mouse P0.5 lenses. Functional classifications of the top 525 identified proteins into gene ontology categories by molecular process and subcellular localization, were adapted for lens. Expression levels of both epithelial and fiber proteomes were compared with their temporal and spatial mRNA levels using E14.5, E16.5, E18.5, and P0.5 RNA-Seq data sets. During this developmental time window, multiple complex biosynthetic and catabolic processes generate the molecular and structural foundation for lens transparency. As expected, crystallins showed a high correlation between their mRNA and protein levels. Comprehensive data analysis confirmed and/or predicted roles for transcription factors (TFs), RNA-binding proteins, translational apparatus including ribosomal heterogeneity and initiation factors, microtubules, cytoskeletal and membrane proteins in lens formation and maturation. Our data highlighted many proteins with unknown function in the lens that were preferentially enriched in epithelium or fibers, setting the stage for future studies to further dissect the roles of these proteins in fiber cell differentiation vs. epithelial cell maintenance. In conclusion, the present proteomic datasets established reference mouse lens epithelium and fiber cell proteomes, provided quantitative analyses of protein and RNA-Seq data, and probed the major proteome remodeling required to form the mature lens fiber cells.
2019-03-05 | PXD009639 | Pride
Project description:Genotype?Tissue Expression atlas of cattle using 7,180 publicly available RNA-sequencing (RNA-seq) samples
2023-02-10 | PRJEB59574 | EVA