ArticleScientific reports2016
A cloud-based workflow to quantify transcript-expression levels in public cancer compendia.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
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- A framework for target discovery in rare cancers.bioRxiv : the preprint server for biology · 2024Article
- A Systematic Identification of RNA-Binding Proteins (RBPs) Driving Aberrant Splicing in Cancer.Biomedicines · 2024Article
- Decoding functional impact of epigenetic regulator mutations on ligand-receptor interaction perturbations for evaluation of cancer immunotherapy.Journal of cellular and molecular medicine · 2024Article
- Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy.Nature cancer · 2024Article
- EPRIM: An approach of identifying cancer immune-related epigenetic regulators.Molecular therapy. Nucleic acids · 2024Article
- Dissecting cellular states of infiltrating microenvironment cells in melanoma by integrating single-cell and bulk transcriptome analysis.BMC immunology · 2023Article
- MED19 encodes two unique protein isoforms that confer prostate cancer growth under low androgen through distinct gene expression programs.Scientific reports · 2023Article
- Survivin Expression in Luminal Breast Cancer and Adjacent Normal Tissue for Immuno-Oncology Applications.International journal of molecular sciences · 2023Article
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- Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Container Profiler: Profiling resource utilization of containerized big data pipelines.GigaScience · 2022Article
- A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses.Communications biology · 2022Article
- Single cell spatial analysis reveals the topology of immunomodulatory purinergic signaling in glioblastoma.Nature communications · 2022Article
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- An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer.Cell reports. Medicine · 2022Article
- recount3: summaries and queries for large-scale RNA-seq expression and splicing.Genome biology · 2021Article
- Article
Corrections and comments
- Commented on byCheap-seq.2016
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Public compendia of sequencing data are now measured in petabytes. Accordingly, it is infeasible for researchers to transfer these data to local computers. Recently, the National Cancer Institute began exploring opportunities to work with molecular data in cloud-computing environments. With this approach, it becomes possible for scientists to take their tools to the data and thereby avoid large data transfers. It also becomes feasible to scale computing resources to the needs of a given analysis. We quantified transcript-expression levels for 12,307 RNA-Sequencing samples from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas. We used two cloud-based configurations and examined the performance and cost profiles of each configuration. Using preemptible virtual machines, we processed the samples for as little as $0.09 (USD) per sample. As the samples were processed, we collected performance metrics, which helped us track the duration of each processing step and quantified computational resources used at different stages of sample processing. Although the computational demands of reference alignment and expression quantification have decreased considerably, there remains a critical need for researchers to optimize preprocessing steps. We have stored the software, scripts, and processed data in a publicly accessible repository (https://osf.io/gqrz9).
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