Covid19 WGS Raw Read files
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ABSTRACT:
PROVIDER: EGAS00001007106 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:The Samples were collected from Saint James's Hospital, Dublin and after informed consent Extracted Genomic DNA samples were prepared and sequenced using the Automated Illumina TruSeq PCR-free methodology.
| EGAS00001007048 | EGA
Project description:The Samples were collected from Saint James's Hospital, Dublin and after informed consent Extracted Genomic DNA samples were prepared and sequenced using the Automated Illumina TruSeq PCR-free methodology. The raw reads aligned with GRCh38 human genome and variant calling has been accomplished by GATK. The resulted GVCF and vcf has been submitted as variant analysis.
| EGAS00001007082 | EGA
Project description:The Samples were collected from Saint James's Hospital, Dublin and after informed consent. RNA-Sequencing library preparation was performed using the Illumina TruSeq Stranded Total RNA Library Prep Globin kit (20020612) with an input amount of 100 – 1000 ng. Library preparation was automated and processed using a Hamilton NGS Star. Library quality was assessed using the Roche KAPA Library Quantification Kit (7960298001) and GX Caliper HS Assay (CLS760672, 760517), run on Roche Lightcycler 480 II and Perkin Elmer LabChip GX Touch analyser respectively. Libraries were pooled and sequenced (75bp PE) on an Illumina NovaSeq 6000 instrument using NovaSeq 6000 S2 Reagent Kit v1.5 (20028314) targeting 50M paired reads. Raw data (BCL format) were demultiplexed and converted to FASTQ format using BCL2FastQ (Illumina). Adapters were trimmed using Skewer (PMID: 24925680) and QC assessed using FASTQC. STAR (PMID: 23104886) was used to align reads to the reference genome (GRCh38/hg38) as well as to the transcriptome (GENCODE v. 25). Quality of the RNA alignment was assessed using Picard QC. Gene and isoform quantification was performed using RSEM (PMID: 21816040). The study shares expression data (gene.results) and chimeric.junction.out.
| EGAS00001007116 | EGA
Project description:A novel one-dimensional on-line pH gradient-eluted strong cation exchange (SCX)-nano-ESI-MS/MS method was developed for protein identification and tested with mixture of six standard proteins, total lysate of HuH7 and N2a cells, as well as membrane fraction of N2a cells. This method utilized an on-line nano-flow SCX column in a nano-LC system coupled with a nano-electrospray high-resolution mass spectrometer. Protein digests were separated on a nano-flow SCX column with a pH gradient and directly introduced into a mass spectrometer through nano-electrospray ionization. SCXLC-MS/MS showed identification capability for higher proportion of basic peptides compared to RPLC-MS/MS method, especially for histidine-containing peptides. Our SCXLC-MS/MS method is an excellent alternative method to the RPLC-MS/MS method for analysis of standard proteins, total cell and membrane proteomes.
2016-01-28 | PXD003438 | Pride
Project description:Human abdominal adipose tissue was obtained with informed consent from a 33-year old Caucasian female (BMI = 32.96 Kg/m2) undergoing lipoaspiration. Adipose stromal cells (hASCs) were isolated and differentiated into adipocytes in vitro.
2010-09-30 | GSE20699 | GEO
Project description:Human abdominal adipose tissue was obtained with informed consent from a 33-year old Caucasian female (BMI = 32.96 Kg/m2) undergoing lipoaspiration. Adipose stromal cells (hASCs) were isolated and differentiated into adipocytes in vitro.
2010-09-30 | GSE20697 | GEO
Project description:Gene Expression Profiling of Oral Squamous Cell Carcinoma (OSCC) was performed to delineate candidate genes clusters with potential to distinguish normal and tumor tissue from oral cavity. All tissue samples were collected after obtaining written informed consent.
2011-10-30 | GSE23558 | GEO
Project description:Background Sequence alignment data is often ordered by coordinate (id of the reference sequence plus position on the sequence where the fragment was mapped) when stored in BAM files, as this simplifies the extraction of variants between the mapped data and the reference or of variants within the mapped data. In this order paired reads are usually separated in the file, which complicates some other applications like duplicate marking or conversion to the FastQ format which require to access the full information of the pairs. Results In this paper we introduce biobambam, a set of tools based on the efficient collation of alignments in BAM files by read name. The employed collation algorithm avoids time and space consuming sorting of alignments by read name where this is possible without using more than a specified amount of main memory. Using this algorithm tasks like duplicate marking in BAM files and conversion of BAM files to the FastQ format can be performed very efficiently with limited resources. We also make the collation algorithm available in the form of an API for other projects. This API is part of the libmaus package. Conclusions In comparison with previous approaches to problems involving the collation of alignments by read name like the BAM to FastQ or duplication marking utilities our approach can often perform an equivalent task more efficiently in terms of the required main memory and run-time. Our BAM to FastQ conversion is faster than all widely known alternatives including Picard and bamUtil. Our duplicate marking is about as fast as the closest competitor bamUtil for small data sets and faster than all known alternatives on large and complex data sets.
| S-EPMC4075596 | biostudies-literature
Project description:Array Comparative Genomic Hybridization (CGH) profiling of Oral Sqaumaous Cell Carcinoma (OSCC) was performed to delineate candidate non-random chromosomal loci associated with clinico-pathological parameters. The array CGH hybridizations were performed for 60 OSCC samples with pooled gender matched controls. All tissue samples were collected after obtaining written informed consent.
2011-03-11 | GSE23831 | GEO