Sanger
Ontology highlight
ABSTRACT:
PROVIDER: EGAO00000001086 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Organisation EGAO00000000080
| EGAO00000000080 | EGA
Project description:SummaryIn the era of next generation sequencing and beyond, the Sanger technique is still widely used for variant verification of inconclusive or ambiguous high-throughput sequencing results or as a low-cost molecular genetical analysis tool for single targets in many fields of study. Many analysis steps need time-consuming manual intervention. Therefore, we present here a pipeline-capable high-throughput solution with an optional Shiny web interface, that provides a binary mutation decision of hotspots together with plotted chromatograms including annotations via flat files.Availability and implementationSangeR is freely available at https://github.com/Neuropathology-Giessen/SangeR and https://hub.docker.com/repository/docker/kaischmid/sange_r.ContactKai.Schmid@patho.med.uni-giessen.de or Daniel.Amsel@patho.med.uni-giessen.de.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9710597 | biostudies-literature
Project description:Aselloidea isopods Sanger sequencing
| PRJEB30668 | ENA
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 29 samples of primary cells or cultured primary cells of different haemopoeitc lineages from cord blood are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001165. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
2015-09-30 | E-MTAB-3819 | biostudies-arrayexpress
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 4 samples of primary cells from tonsil with cell surface markes CD20med/CD38high in young individuals (3 to 10 years old) are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001523. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
2016-05-12 | E-MTAB-4754 | biostudies-arrayexpress
Project description:Sanger sequencing platforms, such as applied biosystems instruments, generate chromatogram files. Generally, for 1 region of a sequence, we use both forward and reverse primers to sequence that area, in that way, we have 2 sequences that need to be aligned and a consensus generated before mutation detection studies. This work is cumbersome and takes time, especially if the gene is large with many exons. Hence, we devised a rapid automated command system to filter, build, and align consensus sequences and also optionally extract exonic regions, translate them in all frames, and perform an amino acid alignment starting from raw sequence data within a very short time. In full capabilities of Automated Mutation Analysis Pipeline (ASAP), it is able to read "*.ab1" chromatogram files through command line interface, convert it to the FASTQ format, trim the low-quality regions, reverse-complement the reverse sequence, create a consensus sequence, extract the exonic regions using a reference exonic sequence, translate the sequence in all frames, and align the nucleic acid and amino acid sequences to reference nucleic acid and amino acid sequences, respectively. All files are created and can be used for further analysis. ASAP is available as Python 3.x executable at https://github.com/aditya-88/ASAP. The version described in this paper is 0.28.
| S-EPMC5066597 | biostudies-literature
Project description:The microarray gene expression pattern was studied using 798 different cancer cell lines. The cancer cell lines are obtained from different centers. Annotation information were provided in the supplementary file.
2015-05-16 | GSE68950 | GEO