Evidence map›Paper›PMID 35037223›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Analysis of Small RNA Sequencing Data in Plants.

Vanika Garg, Rajeev K Varshney

Abstract read
PubMed Publisher
In one paragraph

Article 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.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Rejuvenation of MaturePlants (Basel, Switzerland) · 2025
    Article
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

2 authors.

Vanika GargCenter of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana, India.
Rajeev K VarshneyCenter of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana, India. r.k.varshney@cgiar.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past decades, next-generation sequencing (NGS) has been employed extensively for investigating the regulatory mechanisms of small RNAs. Several bioinformatics tools are available for aiding biologists to extract meaningful information from enormous amounts of data generated by NGS platforms. This chapter describes a detailed methodology for analyzing small RNA sequencing data using different open source tools. We elaborate on various steps involved in analysis, from processing the raw sequencing reads to identifying miRNAs, their targets, and differential expression studies.

Indexed as

High-Throughput Nucleotide SequencingMicroRNAsComputational BiologyPlantsSequence Analysis, RNAMicroRNAsBioinformaticsDifferential expressionmiRDeep-PmiRNAsSmall RNA sequencing

Identifiers

PMID35037223

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.