ArticleGenome biology2017
Data normalization considerations for digital tumor dissection.
Article in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
16 citing papers in PubMed.
- Evaluating deconvolution methods using real bulk RNA-expression data for robust prognostic insights across cancer types.Genome biology · 2026Article
- Dataset including whole blood gene expression profiles and matched leukocyte counts with utility for benchmarking cellular deconvolution pipelines.BMC genomic data · 2024Article
- CD4 T cells and toxicity from immune checkpoint blockade.Immunological reviews · 2023Review
- MTAP loss correlates with an immunosuppressive profile in GBM and its substrate MTA stimulates alternative macrophage polarization.Scientific reports · 2022Article
- Computational Biology Predicts the Efficacy of Tumor Immune Checkpoint Blockade.BioMed research international · 2022Article
- Gene expression profiling-based risk prediction and profiles of immune infiltration in diffuse large B-cell lymphoma.Blood cancer journal · 2021Article
- Benchmarking of cell type deconvolution pipelines for transcriptomics data.Nature communications · 2020Article
- MethylResolver-a method for deconvoluting bulk DNA methylation profiles into known and unknown cell contents.Communications biology · 2020Article
- Tumour-Infiltrating Immune Cell-Based Subtyping and Signature Gene Analysis in Breast Cancer Based on Gene Expression Profiles.Journal of Cancer · 2020Article
- Article
- Immune overdrive signature in colorectal tumor subset predicts poor clinical outcome.The Journal of clinical investigation · 2019Article
- Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data.Genome medicine · 2019Article
- Quantifying tumor-infiltrating immune cells from transcriptomics data.Cancer immunology, immunotherapy : CII · 2018Review
- Benchmarking: contexts and details matter.Genome biology · 2017Article
- Revisit linear regression-based deconvolution methods for tumor gene expression data.Genome biology · 2017Article
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5 authors.
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Abstract
In a recently published article in Genome Biology, Li and colleagues introduced TIMER, a gene expression deconvolution approach for studying tumor-infiltrating leukocytes (TILs) in 23 cancer types profiled by The Cancer Genome Atlas. Methods to characterize TIL biology are increasingly important, and the authors offer several arguments in favor of their strategy. Several of these claims warrant further discussion and highlight the critical importance of data normalization in gene expression deconvolution applications.Please see related Li et al correspondence: www.dx.doi.org/10.1186/s13059-017-1256-5 and Zheng correspondence: www.dx.doi.org/10.1186/s13059-017-1258-3.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.