Geoseq: a tool for dissecting deep-sequencing datasets

Gurtowski J, Cancio A, Shah H, et al. Geoseq: a tool for dissecting deep-sequencing datasets. BMC Bioinformatics. 2010;11(1): 506.Background Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO), Sequence Read Archive (SRA) hosted by the NCBI, or the DNA Data Bank of Japan (ddbj). Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Results Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Conclusions Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a) identify differential isoform expression in mRNA-seq datasets, b) identify miRNAs (microRNAs) in libraries, and identify mature and star sequences in miRNAS and c) to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool

Symmetry of computerised tomography of the brain in traumatic brain injury: a quality improvement audit

Abstract Background Non-contrast Computerised Tomography (NCCT) of brain is the gold standard investigation for diagnosis and management of Traumatic brain injury (TBI). Asymmetrical CT brain images as a result of improper head positioning in the CT gantry will compromise the diagnostic value. Therefore, this audit aimed to assess the degree of asymmetry in CT brain studies carried out in TBI patients. Methods This audit was carried out at a level one trauma centre and included CT scans of TBI patients with a Glasgow come scale (GCS) score ≤ 13, admitted to the Neurological intensive care unit (NICU). The first cycle involved a period of three months. The data collected included demographic data and variables such as GCS at the time of the scan and whether the patient was intubated or not. The visualisation of bilateral internal auditory meatuses was used as landmark to determine scan symmetry. If the internal auditory meatus on both sides were visible on the same slice of CT scan, it was considered symmetric. The degree of asymmetry was gauged based on the axial slice difference between bilateral meatuses. The data collected was tabulated and presented to Neurosurgery residents and a checklist was formulated which had to be followed while positioning the patient on CT table prior to imaging. Results The first cycle of the audit showed that 83.8% of scans were asymmetric and among them 44.1% revealed gross asymmetry affecting interpretation of the scan. Following, implementation of the checklist the percentage of gross asymmetry dropped to 21.86% in the second and to 22.22% in the third audit. Conclusion The use of checklist prior to CT brain studies showed sustainable improvement in reducing gross asymmetry and in acquisition of symmetrical CT brain images

Adherence to Head-of-Bed Elevation in Traumatic Brain Injury: An Audit

Background An important factor affecting the outcome of traumatic brain injury (TBI) is the early management of raised intracranial pressure (ICP). Head-of-bed elevation (HBE) is a simple and effective method to reduce ICP and prevent aspiration in head injury. Methods This audit was carried out in a level one trauma center. All adult TBI patients were included in the study except patients who had relative contraindication to HBE, managed in prone or Trendelenburg position or who were able to be seated themselves. Patients were observed twice daily, to check adherence to HBE. Adequate HBE angle was referred as an angle of 20 to 30 degrees. A digital protractor was used to measure the head-end angle. Following the first audit cycle, after discussion with nursing staff, a bedside checklist was formulated and two postintervention audit cycles were carried out. Results The first cycle showed that 40.35% of patients had inadequate HBE. Following implementation of the checklist, this percentage dropped to 11.27 and 7.5% in the second and third cycles, respectively. Agitation (p-value = 0.038) and Glasgow coma scale at admission (p-value = 0.028) were found to be confounders for adherence to HBE. Conclusion Agitation among mild and moderate TBI patients contributed to noncompliance for HBE. There was an increasing trend in adherence to maintaining adequate HBE following the use of a bedside checklist. Sustainability of improvement was confirmed with third audit cycle

Microarray analysis in B cells among siblings with/without MS - role for transcription factor TCF2

Abstract Background We investigated if global gene expression and transcription networks in B-lymphocytes of siblings with multiple sclerosis (MS) were different from healthy siblings. Results Using virus-transformed immortalized B cells and human whole genome bioarrays with validation using RT-qPCR, we found that in siblings with MS, genes for CXCL10, serpin B1 and FUT4 were up regulated whereas CDC5L, TNFRSF19 and HLA-DR were down regulated, among others; transcription analysis showed two intersecting clusters of transcriptional factors - the larger, governed by the upregulated transcription factor 2 (TCF2) and the smaller network regulated by the downregulated CDC5L. Conclusion No study has linked TCF2 to MS and to better understand the role of TCF2 in MS, studies in larger cohorts are required.</p

Microarray analysis in B cells among siblings with/without MS - role for transcription factor TCF2-0

<p><b>Copyright information:</b></p><p>Taken from "Microarray analysis in B cells among siblings with/without MS - role for transcription factor TCF2"</p><p>http://www.biomedcentral.com/1755-8794/1/2</p><p>BMC Medical Genomics 2008;1():2-2.</p><p>Published online 31 Jan 2008</p><p>PMCID:PMC2227948.</p><p></p> on the left while condition based tree is shown on the top

Microarray analysis in B cells among siblings with/without MS - role for transcription factor TCF2-2

<p><b>Copyright information:</b></p><p>Taken from "Microarray analysis in B cells among siblings with/without MS - role for transcription factor TCF2"</p><p>http://www.biomedcentral.com/1755-8794/1/2</p><p>BMC Medical Genomics 2008;1():2-2.</p><p>Published online 31 Jan 2008</p><p>PMCID:PMC2227948.</p><p></p> by circles while transcription factors are represented as rectangles. Green arrows indicate that the nodes at each end of the arrow are regulated in the same direction (up or down) while the red arrows connect the nodes that are anticorrelated