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Open AccessJournal ArticleDOI

TIMER2.0 for analysis of tumor-infiltrating immune cells

TLDR
TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms.
Abstract
Tumor progression and the efficacy of immunotherapy are strongly influenced by the composition and abundance of immune cells in the tumor microenvironment. Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition from bulk tumor transcriptome profiles. These estimated tumor immune infiltrate populations have been associated with genomic and transcriptomic changes in the tumors, providing insight into tumor-immune interactions. However, such investigations on large-scale public data remain challenging. To lower the barriers for the analysis of complex tumor-immune interactions, we significantly improved our previous web platform TIMER. Instead of just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms. TIMER2.0 provides four modules for investigating the associations between immune infiltrates and genetic or clinical features, and four modules for exploring cancer-related associations in the TCGA cohorts. Each module can generate a functional heatmap table, enabling the user to easily identify significant associations in multiple cancer types simultaneously. Overall, the TIMER2.0 web server provides comprehensive analysis and visualization functions of tumor infiltrating immune cells.

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IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures.

TL;DR: IOBR as mentioned in this paper is a computational tool for effective Immuno-Oncology Biological Research (IOBR), providing a comprehensive investigation of the estimation of reported or user-built signatures, TME deconvolution, and signature construction based on multi-omics data.
Posted ContentDOI

IOBR: Multi-omics Immuno-Oncology Biological Research to decode tumor microenvironment and signatures

TL;DR: A computational tool for effective Immuno-Oncology Biological Research (IOBR), providing comprehensive investigation of estimation of reported or user-built signatures, TME deconvolution and signature construction base on multi-omics data.
Journal ArticleDOI

GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA.

TL;DR: GEPIA2021 as mentioned in this paper is a standalone extension of GEPIA, allowing users to perform multiple interactive analysis based on the deconvolution results, including cell type-level proportion comparison, correlation analysis, differential expression, and survival analysis.
Journal ArticleDOI

CD8+ T cells and fatty acids orchestrate tumor ferroptosis and immunity via ACSL4.

TL;DR: In this article , T cell-derived interferon (IFN)γ in combination with arachidonic acid (AA) induces immunogenic tumor ferroptosis, serving as a mode of action for CD8+ T cell (CTL)-mediated tumor killing.
Journal ArticleDOI

Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.

TL;DR: In this paper, the role of anti-Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA was analyzed using RNA sequencing data obtained from The Cancer Genome Atlas.
References
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Journal ArticleDOI

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
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RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

TL;DR: It is shown that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads, and estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired- end reads, depending on the number of possible splice forms for each gene.
Journal ArticleDOI

Robust enumeration of cell subsets from tissue expression profiles

TL;DR: CIBERSORT outperformed other methods with respect to noise, unknown mixture content and closely related cell types when applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen and fixed tissues, including solid tumors.
Journal ArticleDOI

The cancer genome atlas pan-cancer analysis project

John N. Weinstein, +379 more
- 01 Oct 2013 - 
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
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