ReviewJournal of the Indian Institute of Science2020
Single-Cell RNA Sequencing for Precision Oncology: Current State-of-Art.
Review in Journal of the Indian Institute of Science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 14 citations in OpenAlex.
- New Insights into Colorectal Cancer through the Lens of Precision Oncology and Personalized Medicine: Multi-Omics Helps Aging of Predisposed People.Current aging science · 2025Review
- High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing.Nature communications · 2023Article
- An integrated single-cell transcriptomic dataset for non-small cell lung cancer.Scientific data · 2023Article
- A novel single-cell RNA-sequencing approach and its applicability connecting genotype to phenotype in ageing disease.Scientific reports · 2022Article
- Nutritional Regulation of Mammary Tumor Microenvironment.Frontiers in cell and developmental biology · 2022Review
- Integration of Genomic Profiling and Organoid Development in Precision Oncology.International journal of molecular sciences · 2021Review
- Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine.International journal of molecular sciences · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumors exhibit genetic and phenotypic diversity leading to intra-tumor heterogeneity (ITH). Further complex ecosystem (stromal and immune cells) of tumors contributes into the ITH. This ITH allows tumors to overcome various selection pressures such as anti-cancer therapies and metastasis at distant organs. Single-cell RNA-seq (scRNA-seq) has provided unprecedented insights into ITH and its implications in drug resistance and metastasis. As scRNA-seq technology grows and provides many new findings, new tools on different programming platforms are frequently generated. Here, we aim to provide a framework and guidelines for new entrants into the field of scRNA-seq. In this review, we discuss the current state-of-art of scRNA-seq analysis step-by-step including filtering, normalization and analysis. First, we discuss the brief history of experimental methods, followed by data processing and implications in precision oncology.
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.