ABSTRACT: Genome wide genotype data from C. sativa cultivars. Submitters of each sample generously agreed to have data shared publicly in order to promote research in cannabis.
Project description:When characterizing novel cell lines, we used SNP genotyping alignment to compare the tumor to the resulting cell line. In order to do this pairwise comparison as each cell model was developed, we added additional data from the GEO database during the normalization step. These data were either tumor DNA or cancer cell line DNA. These samples were not part of a matched pair and so genotype alignment was not reported for these samples. The GEO Series and Sample numbers used for each sample grouping is as follows. Wood- Series: GSE21541; Samples: GSM533396, GSM533397, GSM533398, GSM533399, GSM533400, GSM533401, GSM533402, GSM533404, GSM533410. Ferry- Series: GSE16125; Samples: GSM403493, GSM403494, GSM403495, GSM403496, GSM403497, GSM403498, GSM403499, GSM403500, GSM403501. Jacket series 1: GSE15126; samples: GSM385517, GSM385518, GSM385519, GSM385520, GSM385521, GSM385522, GSM385523, GSM385524, GSM385525, GSM385526. Jacket series 2: GSE62407; Samples: GSM1526628, GSM1526648, GSM1526668. DF Series GSE39130; Samples: GSM956523, GSM956524, GSM956525, GSM956526, GSM956527, GSM956528.
Project description:This dataset reports the UPLC-QTof MS untargeted analysis of Vitis vinifera L. leaves, collected from Italy (Trentino) and Germany (Mecklenburg West-Pomerania), from two fungus-resistant grape varieties (PIWI), Regent and Phoenix. For each variety, 40 leaves were sampled from 10 plants (4 leaves/plant) in Italy, and other 40 with the same process in Germany. The leaves from each plant were homogenized and extracted separately, in the same day, under a randomized order. A quality control (QC) sample was prepared by pooling a small aliquot from each sample. </p> The aim of the project, was to use this sample/data set as an illustrative example for the use the pipeline MetaDB (https://github.com/rmylonas/MetaDB). MetaDB has been developed in order to combine, with a user-friendly web based, different bioinformatic tools used in metabolomics, which takes care a) metadata organization, b) creation of randomized sequences including QC sample, c) data quality evaluation, d) data storage organization, e) data analysis and f) submission to public repositories.
Project description:The sequence read archive (SRA) contains over 52 terabases or 482 billion reads from Drosophila melanogaster (as of June 2018). These data are massively underused by the community and include 14,423 RNA-Seq samples, that is roughly 7 times the size of modENCODE. Currently the major challenge is finding high quality datasets that are suitable for inclusion in new studies. To help the community overcome this hurdle, we re-processed all D. melanogaster RNA-Seq SRA experiments (SRXs) using an identical workflow. This workflow uses a data driven approach to identify technical metadata (i.e., strandedness and layout) for each sample in order to optimize mapping parameters. The workflow generates QC metrics, coverage tracks based on the dm6 assembly, and calculates gene level, junction level, and intergenic counts against FlyBase r6.11. This resource will allow any researcher to visualize browser tracks for any publicly available dataset, quickly identify high quality data sets for use in their own research, and download identically processed counts tables. There is a treasure trove of underused data sitting in the SRA and this work addresses the first challenge to make data integration a common laboratory practice.
Project description:In this study, we aim to present a global view of transcriptome dynamics in different rice cultivars (IR64, Nagina 22 and Pokkali) under control and stress conditions. More than 50 million high quality reads were obtained for each tissue sample using Illumina platform. Reference-based assembly was performed for each rice cultivar. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample.
Project description:Comparison of mRNA accumulation in the seedling leaves of 8 unstressed barley cultivars ****[PLEXdb(http://www.plexdb.org) has submitted this series at GEO on behalf of the original contributor, . The equivalent experiment is BB20 at PLEXdb.]
Project description:The project’s primary purpose is to establish a network of Hospice Palliative Care settings using a common and consistent method of assessing and documenting bowel functioning in order to be able to carry out future collaborative studies of constipation treatments. The secondary goal is to gather normative data on current bowel care function and outcomes of current treatments which can be used to determine sample size calculations for future controlled trials of bowel management protocols. In order to complete this goal the project requires a thorough assessment of current nursing practice in regard to bowel care.
Project description:Next-generation sequencing was employed to compare transcriptomic profiling of ovules at and prior to the appearance of nucellar embryony initial cells. To exclude the unwanted genetic background noise and variations among years, two biological replicates for each sample were set by sampling in two consecutive years from two pairs of polyembryonic and monoembryonic cultivars, i.e. one pair of mandarin and the other of grapefruit/pummelo. In that manner, 71 embryo-type enriched transcripts were determined by overlaying differentially expressed transcripts, derived from pairwise comparisons between polyembryonic and monoembryonic cultivars in each basic taxa, which revealed commonly genes that indeed regulated nucellar embryogenesis. Transcriptome profiling indicated that cell wall remodelling transcripts, such as pectinesterase, endochitinase, glucan endo-1,3-β-glucosidase precursor, UDP-glucosyltransferase and laccase were significantly enriched in the polyembryonic cultivars. The expression of transcription factors containing AP2/ERF and WRKY domains were also up-regulated in polyembryonic cultivars compared with monoembryonic cultivars. In addition, the embryo-type enriched transcripts were associated with hormone regulation and signal transduction, as well as carbohydrate metabolism.
Project description:DNA methylation is a complex epigenetic marker that can be analysed using a wide variety of methods. Interpretation and visualisation of DNA methylation data can mask complexity in terms of methylation status at each CpG site, cellular heterogeneity of samples and allelic DNA methylation patterns within a given DNA strand. Bisulfite sequencing is considered the gold standard, however visualisation of massively parallel sequencing results remains a significant challenge. We created a program called Methpat that facilitates visualisation and interpretation of bisulfite sequencing data generated by massively parallel sequencing. To demonstrate this, we performed multiplex PCR that targeted 48 regions of interest across 95 human samples. The regions selected included known gene promoters associated with cancer, repetitive elements, known imprinted regions and mitochondrial genomic sequences. We interrogated a range of samples including human cell lines, primary tumours and primary tissue samples. Methpat generates two forms of output: a tab delimited text file for each sample that summarises DNA methylation patterns and their read counts for each amplicon and a HTML file that summarises this data visually. Methpat can be used with publicly available whole genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) datasets with sufficient read depths. Using Methpat, complex DNA methylation data derived from massively parallel sequencing can be summarised and visualised for biological interpretation. By accounting for allelic DNA methylation states and their abundance in a sample, Methpat can unmask the complexity of DNA methylation and reveal further biological insight in existing datasets.