ReviewDevelopment (Cambridge, England)2020
A primer for generating and using transcriptome data and gene sets.
Review in Development (Cambridge, England), 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.
- Genetic and behavioral analyses suggest that larval and adult stages of Lucilia cuprina employ different sensory systems to detect rotten beef.Parasites & vectors · 2025Article
- Relieving effect of an Maren-Zhizhu emulsion on loperamide hydrochloride-induced constipation in mice and its effects on the gut microbiota.Frontiers in microbiology · 2025Article
- Melatonin Receptor Expression in Primary Uveal Melanoma.International journal of molecular sciences · 2024Article
- Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake.Microbiome · 2024Article
- CD56Frontiers in immunology · 2024Article
- Bulk and Single-Cell RNA-Seq Analyses for Studies of Spermatogonia.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Identification and Cloning of a CC-NBS-NBS-LRR Gene as a Candidate ofInternational journal of molecular sciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Transcriptomic approaches have provided a growing set of powerful tools with which to study genome-wide patterns of gene expression. Rapidly evolving technologies enable analysis of transcript abundance data from particular tissues and even single cells. This Primer discusses methods that can be used to collect and profile RNAs from specific tissues or cells, process and analyze high-throughput RNA-sequencing data, and define sets of genes that accurately represent a category, such as tissue-enriched or tissue-specific gene expression.
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.