EasyPairedTag: A Comprehensive Pipeline for Paired-Tag Data Quality Control and Analysis
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ABSTRACT:
PROVIDER: PRJNA1281414 | ENA |
REPOSITORIES: ENA
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Project description:Paired-Tag is an ultra-high throughput single-cell method for simultaneous profiling of gene expression and histone modifications, enabling identification of cell-type-specific cis-regulatory elements and correlation of their chromatin states with the expression levels of putative target genes. However, the lack of an automated end-to-end pipeline has limited its application. Here, we present easyPairedTag, a Snakemake pipeline for Paired-Tag data processing and quality control. Key features include flexible configuration for diverse experimental setups, automated sub-library merging and sample demultiplexing, and comprehensive quality control metrics. When applied to published mouse brain datasets, easyPairedTag improves overlapping gene quantification via strand-specific analysis for precise cell clustering. In mouse hypothalamus datasets, easyPairedTag is compatible with the processing of paired-end sequencing data to detect histone modification peaks with higher sensitivity and specificity, facilitating the discovery of putitive cell-type-specific cis-regulatory elements.
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Project description:Somatic genome rearrangements are thought to play important roles in cancer development. We optimized a long span paired-end-tag (PET) sequencing approach using 10 Kb genomic DNA inserts to study human genome structural variations (SVs). The use of 10 Kb insert size allows the identification of breakpoints within repetitive or homology containing regions of a few Kb in size and results in a higher physical coverage compared to small insert libraries with the same sequencing effort. We have applied this approach to comprehensively characterize the SVs of 15 cancer and 2 non-cancer genomes and used a filtering approach to strongly enrich for somatic SVs in the cancer genomes. Our analyses revealed that most inversions, deletions, and insertions are germline SVs, whereas tandem duplications, unpaired inversions, inter-chromosomal translocations, and complex rearrangements are overrepresented among somatic rearrangements in cancer genomes. We demonstrate that the quantitative and connective nature of DNA-PET data is precise in delineating the genealogy of complex rearrangement events, we observe signatures which are compatible with breakage-fusion-bridge cycles, and discover that large duplications are among the initial rearrangements that trigger genome instability for extensive amplification in epithelial cancers. Structural variations of 15 human cancer samples and 2 human normal samples were identified by long span paired-end sequencing
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Project description:Background RNA-Seq analysis has become a routine task in numerous genomic research labs, driven by the reduced cost of bulk RNA sequencing experiments. These studies generate billions of reads that require easy-to-run, comprehensive, and reproducible analysis. However, many labs rely on in-house scripts, which can be challenging for bench scientist to use and hinder standardization and reproducibility. While existing RNA-Seq pipelines attempt to address these challenges, they often lack a complete end-to-end user interface. Findings To bridge this gap, we developed RNA-SeqEZPZ, an automated pipeline with a user-friendly point-and-click interface, enabling rigorous and reproducible RNA-Seq analysis without requiring programming or bioinformatics expertise. For advanced users, the pipeline can also be executed from the command line, allowing customization of steps to suit specific applications. The innovation of this pipeline lies in the combination of three key features: (1) all software is packaged within a Singularity container, eliminating installation issues, (2) it offers a point-and-click interface from raw FASTQ files through differential expression and pathway analysis, and (3) it includes a Nextflow version, enabling scalability and portability for seamless execution across various platforms including job submission in the cloud and cluster computing. Additionally, RNA-SeqEZPZ generates a thorough statistical report and offers an option for batch adjustment to minimize effects of noise due to technical variations across replicates. Reports can also be reviewed by a bioinformatician to ensure the overall quality of the analysis. Conclusions RNA-SeqEZPZ is a robust, accessible, and scalable solution for comprehensive RNA-Seq analysis, enabling researchers to focus on biological insights rather than computational challenges.
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Project description:Strand-specific massively-parallel cDNA sequencing (RNA-Seq) is a powerful tool for novel transcript discovery, genome annotation, and expression profiling. Despite multiple published methods for strand-specific RNA-Seq, no consensus exists as to how to choose between them. Here, we developed a comprehensive computational pipeline for the comparison of library quality metrics from any RNA-Seq method. Using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark, we compared seven library construction protocols, including both published and our own novel methods. We found marked differences in complexity, strand-specificity, evenness and continuity of coverage, agreement with known annotations, and accuracy for expression profiling. Weighing each method’s performance and ease, we identify the dUTP second strand marking and the Illumina RNA ligation methods as the leading protocols, with the former benefitting from the availability of paired-end sequencing. Our analysis provides a comprehensive benchmark, and our computational pipeline is applicable for assessment of future protocols in any organism.
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Project description:Somatic genome rearrangements are thought to play important roles in cancer development. We optimized a long span paired-end-tag (PET) sequencing approach using 10 Kb genomic DNA inserts to study human genome structural variations (SVs). The use of 10 Kb insert size allows the identification of breakpoints within repetitive or homology containing regions of a few Kb in size and results in a higher physical coverage compared to small insert libraries with the same sequencing effort. We have applied this approach to comprehensively characterize the SVs of 15 cancer and 2 non-cancer genomes and used a filtering approach to strongly enrich for somatic SVs in the cancer genomes. Our analyses revealed that most inversions, deletions, and insertions are germline SVs, whereas tandem duplications, unpaired inversions, inter-chromosomal translocations, and complex rearrangements are overrepresented among somatic rearrangements in cancer genomes. We demonstrate that the quantitative and connective nature of DNA-PET data is precise in delineating the genealogy of complex rearrangement events, we observe signatures which are compatible with breakage-fusion-bridge cycles, and discover that large duplications are among the initial rearrangements that trigger genome instability for extensive amplification in epithelial cancers.
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