Evidence map›Paper›PMID 32926366›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2021

Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments.

Xiaoqing Yu, Farnoosh Abbas-Aghababazadeh, Y Ann Chen, Brooke L Fridley

Abstract readReview
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  19. Nuclear Isolation from Cryopreserved In Vitro Derived Blood Cells.Journal of visualized experiments : JoVE · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xiaoqing YuDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
Farnoosh Abbas-AghababazadehDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
Y Ann ChenDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
Brooke L FridleyDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA. Brooke.Fridley@moffitt.org.

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI Christine O'Connell · 1998 to 2026
$93.5M
NCI NIH HHS P30 CA076292
6 · The paper itself

Abstract

High-throughput sequencing (HTS) has revolutionized researchers' ability to study the human transcriptome, particularly as it relates to cancer. Recently, HTS technology has advanced to the point where now one is able to sequence individual cells (i.e., "single-cell sequencing"). Prior to single-cell sequencing technology, HTS would be completed on RNA extracted from a tissue sample consisting of multiple cell types (i.e., "bulk sequencing"). In this chapter, we review the various bioinformatics and statistical methods used in the processing, quality control, and analysis of bulk and single-cell RNA sequencing methods. Additionally, we discuss how these methods are also being used to study tumor heterogeneity.

Indexed as

Computational BiologyDatabases, GeneticData Interpretation, StatisticalGene Expression ProfilingHumansNeoplasmsQuality ControlSequence Analysis, RNASingle-Cell AnalysisSkin NeoplasmsDifferential expressionHigh-throughput sequencingNormalizationQuality controlSingle-cellTranscriptomicsTumor heterogeneity

Identifiers

PMID32926366
PMCPMC7771369

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Registered trials

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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.