Project description:In recent years, there has been a major expansion in digital storage capability for hosting raw diffraction datasets. Naturally, the question has now arisen as to the benefits and costs for the preservation of such raw, i.e., experimental diffraction datasets. We describe the consultations made of the global structural chemistry, i.e., chemical crystallography community from the points of view of the International Union of Crystallography (IUCr) Committee on Data, of which JRH was the Chair until very recently, and the IUCrData Raw Data Letters initiative, for which LKB is the Main Editor. The monitoring by the CCDC of CSD depositions which cite the digital object identifiers of raw diffraction datasets provides interesting statistics by probe (x-ray, neutron, or electron) and by home lab vs central facility. Clearly, a better understanding of the reproducibility of current analysis procedures is at hand. Policies for publication requiring raw data have been updated in IUCr Journals for macromolecular crystallography, namely, that raw data should be made available for a new crystal structure or a new method as well as the wwPDB deposition. For chemical crystallography, such a step requiring raw data archiving has not yet been recommended by the IUCr Commission on Structural Chemistry.
Project description:PTSD - Posttraumatic stress disorder. 33 samples taken from PMBCs of survivors of psychological trauma, in two time points: in ER, few hours after the truma, and four months later. Some of the patients devepled chronic PTSD (17 samples) and others recovered and set to be the Control group (16 samples). This is the raw data consists of 12,600 probes from U95A chip. Samples are labeled with 3 tags: P/C for PTSD or Control, ER/M4 - for time point of sample, D/ND for Decrement or Non-decrement symptoms over time. (e.g. sample 23C-M4-D was taken 4 months after trauma from patient 23 which belongs to the control group and showed decrease in symptoms) . Samples include the expression value, the GeneBank accession number and Affymetrix indication of valid calls. Keywords: other
Project description:RNA sequencing (RNA-seq) has become an exemplary technology in modern biology and clinical science. Its immense popularity is due in large part to the continuous efforts of the bioinformatics community to develop accurate and scalable computational tools to analyze the enormous amounts of transcriptomic data that it produces. RNA-seq analysis enables genes and their corresponding transcripts to be probed for a variety of purposes, such as detecting novel exons or whole transcripts, assessing expression of genes and alternative transcripts, and studying alternative splicing structure. It can be a challenge, however, to obtain meaningful biological signals from raw RNA-seq data because of the enormous scale of the data as well as the inherent limitations of different sequencing technologies, such as amplification bias or biases of library preparation. The need to overcome these technical challenges has pushed the rapid development of novel computational tools, which have evolved and diversified in accordance with technological advancements, leading to the current myriad of RNA-seq tools. These tools, combined with the diverse computational skill sets of biomedical researchers, help to unlock the full potential of RNA-seq. The purpose of this review is to explain basic concepts in the computational analysis of RNA-seq data and define discipline-specific jargon.