ReviewNature protocols2023
Tutorial: integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMA.
Review in Nature protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- ClonalLife science alliance · 2026Article
- Smyca-FOXM1 ribonucleoprotein complex promotes homologous recombination and tumor immune evasion to define a therapeutic target of triple-negative breast cancer.Journal of biomedical science · 2026Article
- Multi-omic characterization of 14q deletion in renal clear cell carcinoma identifiesJournal for immunotherapy of cancer · 2026Article
- Refined variant calling pipeline on RNA-seq data of breast cancer cell lines without matched-normal samples.BMC research notes · 2025Article
- Hepatic fibroblast growth factor 21 is required for curcumin or resveratrol in exerting their metabolic beneficial effect in male mice.Nutrition & diabetes · 2025Article
- Enhancing immuno-oncology investigations through multidimensional decoding of tumor microenvironment with IOBR 2.0.Cell reports methods · 2024Article
- Recent trends and impact of localized surface plasmon resonance (LSPR) and surface-enhanced Raman spectroscopy (SERS) in modern analysis.Journal of pharmaceutical analysis · 2024Review
- Using a pan-cancer atlas to investigate tumour associated macrophages as regulators of immunotherapy response.Nature communications · 2024Article
- Review
- Reusable tutorials for using cloud-based computing environments for the analysis of bacterial gene expression data from bulk RNA sequencing.Briefings in bioinformatics · 2024Article
- Historical perspective and future directions: computational science in immuno-oncology.Journal for immunotherapy of cancer · 2024Review
- Peripheral blood TCR clonotype diversity as an age-associated marker of breast cancer progression.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors at 4 institutions in 2 countries.
Funding
Abstract
RNA-sequencing (RNA-seq) has become an increasingly cost-effective technique for molecular profiling and immune characterization of tumors. In the past decade, many computational tools have been developed to characterize tumor immunity from gene expression data. However, the analysis of large-scale RNA-seq data requires bioinformatics proficiency, large computational resources and cancer genomics and immunology knowledge. In this tutorial, we provide an overview of computational analysis of bulk RNA-seq data for immune characterization of tumors and introduce commonly used computational tools with relevance to cancer immunology and immunotherapy. These tools have diverse functions such as evaluation of expression signatures, estimation of immune infiltration, inference of the immune repertoire, prediction of immunotherapy response, neoantigen detection and microbiome quantification. We describe the RNA-seq IMmune Analysis (RIMA) pipeline integrating many of these tools to streamline RNA-seq analysis. We also developed a comprehensive and user-friendly guide in the form of a GitBook with text and video demos to assist users in analyzing bulk RNA-seq data for immune characterization at both individual sample and cohort levels by using RIMA.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.