Evidence map›Paper›PMID 34160799›Full record

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

Bioinformatic Pipelines to Analyze lncRNAs RNAseq Data.

Luca Agnelli, Stefania Bortoluzzi, Giancarlo Pruneri

Abstract read
PubMed Publisher
In one paragraph

Article 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 36% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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

3 authors at 2 institutions in 1 country.

Luca AgnelliDepartment of Pathology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy. luca.agnelli@istitutotumori.mi.it.
Stefania BortoluzziDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Giancarlo PruneriDepartment of Pathology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Fondazione IRCCS Istituto Nazionale dei Tumori · ITUniversity of Padua · IT

Funding

Cancer Research UK 29374
6 · The paper itself

Abstract

RNA-sequencing could be nowadays considered the gold standard to study the coding and noncoding transcriptome. The great advantage of high-throughput sequencing in the characterization and quantification of long noncoding RNA (lncRNA) resides in its capability to capture the complexity of lncRNA transcripts configuration patterns, even in the presence of several alternative isoforms, with superior accuracy and discovery power compared to other technologies such as microarrays or PCR-based methods. In this chapter, we provide a protocol for lncRNA analysis using through high-throughput sequencing, indicating the main difficulties in the annotation pipeline and showing how an accurate evaluation of the procedure can help to minimize biased observations.

Indexed as

Sequence Analysis, RNATranscriptomeAlgorithmsComputational BiologyDatabases, GeneticData Interpretation, StatisticalGene Expression ProfilingHigh-Throughput Nucleotide SequencingMolecular Sequence AnnotationRNA, Long NoncodingSoftwareUser-Computer InterfaceWeb BrowserRNA, Long NoncodinglncRNA quantificationRNA sequencingSequencing data mapping

Identifiers

PMID34160799
OpenAlexW3177026978

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.