ABSTRACT: RNA Sequencing using Illumina’s TruSeq Stranded Total RNA with RiboZero Globin depletion library pre kit and sequencing on the NovaSeq 6000.
Project description:RNA Sequencing using Illumina’s TruSeq Stranded Total RNA with RiboZero Globin depletion library pre kit and sequencing on the NovaSeq 6000.
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.
Project description:SummaryDespite the improvement in variant detection algorithms, visual inspection of the read-level data remains an essential step for accurate identification of variants in genome analysis. We developed BamSnap, an efficient BAM file viewer utilizing a graphics library and BAM indexing. In contrast to existing viewers, BamSnap can generate high-quality snapshots rapidly, with customized tracks and layout. As an example, we produced read-level images at 1000 genomic loci for >2500 whole-genomes.Availability and implementationBamSnap is freely available at https://github.com/parklab/bamsnap.Supplementary informationSupplementary data are available at Bioinformatics online.
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.
Project description:We performed RNA-seq experiments on three biological replicates of HeLa cells depleted of MATR3, PTBP1/2, controls, or combined depletion of MATR3/PTBP1/2. Cells were fractionated into cytoplasmic and nuclear RNA. Library preparation was done with the TruSeq stranded RNAseq library kit (Illumina) according to manufacturer’s recommendations; RNA was depleted of rRNA using the RiboZero kit (Epicentre). All libraries were sequenced on Illumina HiSeq2 machines in a single-end manner with a read length of 100 nt.
Project description:To analyse the transcriptional response of Rhodococcus aetherivornas BCP1 to arsenic, RNA was extracted from BCP1 cultures exposed to arsenite [As(III)] 5 mM and arsenate [As(V)] 30 mM for 18 hours in the presence of glucose as only carbon and energy source. Control cultures were carried out without adding any arsenic oxyanions. Illumina Truseq stranded mRNA libraries were constructed after rRNA depletion via Illumina Ribozero and sequenced on Illumina HiSeq 1500 system 2 x 70nt PE rapid mode.
