RACS: Rapid Analysis of ChIP-Seq data for contig based genomes
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ABSTRACT:
PROVIDER: PRJNA516862 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8482030.fastq.gz | Fastqsanger.gz | |||
| SRR8482023.fastq.gz | Fastqsanger.gz | |||
| SRR8482024.fastq.gz | Fastqsanger.gz | |||
| SRR8482025.fastq.gz | Fastqsanger.gz | |||
| SRR8482026.fastq.gz | Fastqsanger.gz |
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Project description:The biological samples are from untagged Tetrahymena thermophila to be used as a control for unspecific binding. Whole cells extracts were crosslinked and immunoprecipitated using M2 affinity gel (Sigma). The obtained DNA was sequenced by HiSeq2500 (Illumina). The processed fastq files were analyzed by RACS that segregates the found read accumulations between genic and intergenic regions being highly efficient for rapid downstream analyses.
2019-09-03 | GSE125576 | GEO
Project description:BackgroundChromatin immunoprecipitation coupled to next generation sequencing (ChIP-Seq) is a widely-used molecular method to investigate the function of chromatin-related proteins by identifying their associated DNA sequences on a genomic scale. ChIP-Seq generates large quantities of data that is difficult to process and analyze, particularly for organisms with a contig-based sequenced genomes that typically have minimal annotation on their associated set of genes other than their associated coordinates primarily predicted by gene finding programs. Poorly annotated genome sequence makes comprehensive analysis of ChIP-Seq data difficult and as such standardized analysis pipelines are lacking.ResultsWe present a one-stop computational pipeline, "Rapid Analysis of ChIP-Seq data" (RACS), that utilizes traditional High-Performance Computing (HPC) techniques in association with open source tools for processing and analyzing raw ChIP-Seq data. RACS is an open source computational pipeline available from any of the following repositories https://bitbucket.org/mjponce/RACS or https://gitrepos.scinet.utoronto.ca/public/?a=summary&p=RACS . RACS is particularly useful for ChIP-Seq in organisms with contig-based genomes that have poor gene annotation to aid protein function discovery.To test the performance and efficiency of RACS, we analyzed ChIP-Seq data previously published in a model organism Tetrahymena thermophila which has a contig-based genome. We assessed the generality of RACS by analyzing a previously published data set generated using the model organism Oxytricha trifallax, whose genome sequence is also contig-based with poor annotation.ConclusionsThe RACS computational pipeline presented in this report is an efficient and reliable tool to analyze genome-wide raw ChIP-Seq data generated in model organisms with poorly annotated contig-based genome sequence. Because RACS segregates the found read accumulations between genic and intergenic regions, it is particularly efficient for rapid downstream analyses of proteins involved in gene expression.
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Project description:Contig-level assemblies of Y chromosomes
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Project description:Shotgun protein sequencing with meta-contig assembly.
Full-length de novo sequencing from tandem mass (MS/MS) spectra of unknown proteins such as antibodies or proteins from organisms with unsequenced genomes remains a challenging open problem. Conventional algorithms designed to individually sequence each MS/MS spectrum are limited by incomplete peptide fragmentation or low signal to noise ratios and tend to result in short de novo sequences at low sequencing accuracy. Our shotgun protein sequencing (SPS) approach was developed to ameliorate these limitations by first finding groups of unidentified spectra from the same peptides (contigs) and then deriving a consensus de novo sequence for each assembled set of spectra (contig sequences). But whereas SPS enables much more accurate reconstruction of de novo sequences longer than can be recovered from individual MS/MS spectra, it still requires error-tolerant matching to homologous proteins to group smaller contig sequences into full-length protein sequences, thus limiting its effectiveness on sequences from poorly annotated proteins. Using low and high resolution CID and high resolution HCD MS/MS spectra, we address this limitation with a Meta-SPS algorithm designed to overlap and further assemble SPS contigs into Meta-SPS de novo contig sequences extending as long as 100 amino acids at over 97% accuracy without requiring any knowledge of homologous protein sequences. We demonstrate Meta-SPS using distinct MS/MS data sets obtained with separate enzymatic digestions and discuss how the remaining de novo sequencing limitations relate to MS/MS acquisition settings.
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Project description:The consequences of rapid mating system evolution in crucifer genomes
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Project description:Rapid High-Resolution Functional Mapping of Yeast Genomes by Saturated Transposition
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Project description:Baltic ringed seal contig-level genome assembly
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Project description:Saimaa ringed seal contig-level genome assembly
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Project description:Contig assembly for tetraploid A. arenosa (ssp arenosa) from south Sweden
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Project description:BackgroundNext generation sequencing technology has allowed efficient production of draft genomes for many organisms of interest. However, most draft genomes are just collections of independent contigs, whose relative positions and orientations along the genome being sequenced are unknown. Although several tools have been developed to order and orient the contigs of draft genomes, more accurate tools are still needed.ResultsIn this study, we present a novel reference-based contig assembly (or scaffolding) tool, named as CAR, that can efficiently and more accurately order and orient the contigs of a prokaryotic draft genome based on a reference genome of a related organism. Given a set of contigs in multi-FASTA format and a reference genome in FASTA format, CAR can output a list of scaffolds, each of which is a set of ordered and oriented contigs. For validation, we have tested CAR on a real dataset composed of several prokaryotic genomes and also compared its performance with several other reference-based contig assembly tools. Consequently, our experimental results have shown that CAR indeed performs better than all these other reference-based contig assembly tools in terms of sensitivity, precision and genome coverage.ConclusionsCAR serves as an efficient tool that can more accurately order and orient the contigs of a prokaryotic draft genome based on a reference genome. The web server of CAR is freely available at http://genome.cs.nthu.edu.tw/CAR/ and its stand-alone program can also be downloaded from the same website.
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