ReviewMethods in molecular biology (Clifton, N.J.)2022
Sequences to Differences in Gene Expression: Analysis of RNA-Seq Data.
Review in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 4 citations in OpenAlex.
- Immune-stromal dysregulation and senescence in chronic spontaneous urticaria.The journal of allergy and clinical immunology. Global · 2026Article
- Transcriptomics Reveals the Molecular Basis for Methyl Jasmonate to Promote the Synthesis of Monoterpenoids inCurrent issues in molecular biology · 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
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA-Seq is now a routinely employed assay to measure gene expression. As the technique matured over the last decade, so have dedicated analytic tools. In this chapter, we first describe the mainstream as well as the most up-to-date protocols and their implications on downstream analysis. We then detail the steps entailing RNA-Seq analysis in three main stages: (i) preprocessing and data preparation, (ii) upstream processing, and (iii) high-level analyses. We review the most recent and relevant tools as one workflow following a stepwise order. The chapter further encompasses in-depth features of these tools. Details of the required code are made available throughout the chapter, as well as of the underlying statistics. We illustrate these steps with analysis of publicly available RNA-Seq data.
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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.