BAMscale: quantification of DNA sequencing peaks and generation of scaled coverage tracks
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA543507 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We present a tool for processing NGS DNA-seq BAM files to quantify peaks and create coverage tracks from ChIP-seq, NS-seq, ATAC-seq, OK-seq, END-seq and replication timing data
2020-05-17 | GSE131417 | GEO
Project description: Not available
| S-EPMC7175505 | biostudies-literature
Project description:Due to the large size, complex splicing and wide dynamic range of eukaryotic transcriptomes, RNA sequencing samples the majority of expressed genes infrequently, resulting in sparse sequencing coverage that can hinder robust isoform assembly and quantification. Targeted RNA sequencing addresses this challenge by using oligonucleotide probes to capture selected genes or regions of interest for focused sequencing. This enhanced sequencing coverage confers sensitive gene discovery, robust transcript assembly and accurate gene quantification. Here we describe a detailed protocol for all stages of targeted RNA sequencing, from initial probe design considerations, capture of targeted genes, to final assembly and quantification of captured transcripts. Initial probe design and final analysis can take less than a day, while the central experimental capture stage requires ~7 days. Targetted RNA sequencing of long noncoding RNAs
2014-03-01 | E-GEOD-52503 | biostudies-arrayexpress
Project description:Due to the large size, complex splicing and wide dynamic range of eukaryotic transcriptomes, RNA sequencing samples the majority of expressed genes infrequently, resulting in sparse sequencing coverage that can hinder robust isoform assembly and quantification. Targeted RNA sequencing addresses this challenge by using oligonucleotide probes to capture selected genes or regions of interest for focused sequencing. This enhanced sequencing coverage confers sensitive gene discovery, robust transcript assembly and accurate gene quantification. Here we describe a detailed protocol for all stages of targeted RNA sequencing, from initial probe design considerations, capture of targeted genes, to final assembly and quantification of captured transcripts. Initial probe design and final analysis can take less than a day, while the central experimental capture stage requires ~7 days.
2014-03-01 | GSE52503 | GEO
Project description: Not available
| S-EPMC6553860 | biostudies-literature
Project description:We report a new immunoprecipitation-coupled sequencing (DIP-Seq) application termed U-DNA-Seq, where a tailored and catalytically inactive uracil-DNA glycosylase (UNG) was used as uracil-DNA sensor to immunoprecipitate uracil containing genomic DNA fragments. Genomic uracil was profiled in drug-treated (5-fluoro-2'-deoxyuridine (5FdUR) or raltitrexed (RTX)) or non-treated (NT) HCT116 cells expressing the UNG inhibitor (UGI). The same experiments were also performed in the mismatch repair proficient version of the HCT116 cells (HCT116MMR), where chromosome 3 is reinserted to restore functional MMR (PMID: 8044777). Moreover, wild-type HCT116 or K562 cells were also measured. We found that regions of uracil enrichment in this assay were rather broad as compared to the sharp peaks typical in ChIP-seq. Therefore, we applied an approach alternative to the conventional peak calling. Namely, we calculated genome scaled coverage tracks and log2 ratio tracks of the enriched versus the input samples using deepTools package (bamCoverage and bigwigCompare tools, respectively) to provide a more appropriate description of uracil-enriched genomic regions. Interval (bed) files were also derived from these log2 ratio tracks to be able to screen large datasets for colocalizing features with them. For wider context of the study, see the related publication.
2020-09-20 | GSE126822 | GEO
Project description:Fibroblasts rely on adhesive structures to migrate. It is generally thought that adhesive structures disassemble once at the rear of the cell to release the cell and allow further movement. However, a significant portion of adhesions is not disassembled and is instead left on the substrate. We observed that virtually all the non-resorbed adhesions remain connected to the substrate by the means of integrin β5. Forward cell migration results in plasma membrane pulling giving rise to tubular structures that are then left on the ground, forming a network of lipid tracks that persist for several days, thus altering substrate’s topography. Cancer cells of different origin exploit fibroblast-tracks as migration railways. The adhesion of cancer cells along tracks is not mediated by focal adhesions, but rather by frustrated clathrin-coated structures (CCSs). Analysis of the composition of track generated by cancer associated fibroblasts allowed to identify integrin αv as the receptor on cancer cells responsible for track recognition. Some cancer cell lines are not able to perform durotaxis (rigidity driven migration), while fibroblasts are very good at it. We thus tested whether, in the presence of fibroblast-tracks, non-durotactic cancer cells would become durotactic by following tracks and this was indeed the case. Hence, fibroblast-tracks are a novel structure capable of physically directing cell migration of different cell types.
2023-09-22 | PXD034091 | Pride
Project description:LRGASP challenge WTC11 ssCAGE sequencing derived peaks
| PRJNA771361 | ENA
Project description:Alternative splicing is widely acknowledged to be a crucial regulator of gene expression and is a key contributor to both normal developmental processes and disease states. While cost-effective and accurate for quantification, short-read RNA-seq lacks the ability to resolve full-length transcript isoforms despite increasingly sophisticated computational methods. Long-read sequencing platforms such as Pacific Biosciences (PacBio) and Oxford Nanopore (ONT) bypass the transcript reconstruction challenges of short-reads. Here we describe TALON, the ENCODE4 pipeline for analyzing PacBio cDNA and ONT direct-RNA transcriptomes. We apply TALON to three human ENCODE Tier 1 cell lines and show that while both technologies perform well at full-transcript discovery and quantification, each technology has its distinct artifacts. We further apply TALON to mouse cortical and hippocampal transcriptomes and find that a substantial proportion of neuronal genes have more reads associated with novel isoforms than annotated ones. The TALON pipeline for technology-agnostic, long-read transcriptome discovery and quantification tracks both known and novel transcript models as well as expression levels across datasets for both simple studies and larger projects such as ENCODE that seek to decode transcriptional regulation in the human and mouse genomes to predict more accurate expression levels of genes and transcripts than possible with short-reads alone.
2019-06-15 | GSE132766 | GEO
Project description:Background: Small ncRNAs (sncRNAs) offer great hope as biomarkers of disease and response to treatment. This has been highlighted in the context of several medical conditions such as cancer, liver disease, cardiovascular disease, and central nervous system disorders, among many others. Here we assessed several steps involved in the development of an ncRNA biomarker discovery pipeline, ranging from sample preparation to bioinformatic processing. At each stage, we evaluated the pros and cons of different techniques that may be suitable for different experimental designs. Evaluation methods included quality of data output in relation to hands-on laboratory time, cost, and efficiency of processing. Results: Our results show that good quality sequencing libraries can be prepared from small amounts of total RNA and that varying degradation levels in the samples do not have a significant effect on the overall quantification of sncRNAs via NGS. In addition, we describe the strengths and limitations of three commercially available library preparation methods: (1) Novex TBE PAGE gel; (2) Pippin Prep automated gel system; and (3) AMPure XP beads. We describe our bioinformatics pipeline, provide recommendations for sequencing coverage, and describe in detail the expression and distribution of all sncRNAs in four human tissues: whole-blood, brain, heart and liver. Conclusions: Ultimately this study provides tools and outcome metrics that will aid researchers and clinicians in choosing an appropriate and effective high-throughput sequencing quantification method for various study designs, and overall generating valuable information that can contribute to our understanding of small ncRNAs as potential biomarkers and mediators of biological functions and disease.
2015-07-20 | GSE69825 | GEO