Evidence map›Paper›PMID 32795263›Full record

ArticleBMC bioinformatics2020

SQMtools: automated processing and visual analysis of 'omics data with R and anvi'o.

Fernando Puente-Sánchez, Natalia García-García, Javier Tamames

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

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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

3 authors.

Fernando Puente-SánchezSystems Biology Department, Centro Nacional de Biotecnología (CNB-CSIC), C/ Darwin n° 3, Campus de Cantoblanco, 28049, Madrid, Spain. fpusan@gmail.com.ORCID http://orcid.org/0000-0002-6341-3692
Natalia García-GarcíaSystems Biology Department, Centro Nacional de Biotecnología (CNB-CSIC), C/ Darwin n° 3, Campus de Cantoblanco, 28049, Madrid, Spain.
Javier TamamesSystems Biology Department, Centro Nacional de Biotecnología (CNB-CSIC), C/ Darwin n° 3, Campus de Cantoblanco, 28049, Madrid, Spain.

Funding

Ministerio de Ciencia, Innovación y Universidades IJC2018-035180-IMinisterio de Ciencia, Innovación y Universidades SEV-2013-0347-17-2Ministerio de Economía, Industria y Competitividad, Gobierno de España CTM2016-80095-C2-1-RMinisterio de Economía, Industria y Competitividad, Gobierno de España PID2019-110011RB-C31
6 · The paper itself

Abstract

backgroundThe dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, non-specialists are faced with the double challenge of choosing among an ever-increasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches.

resultsHere we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi'o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment.

conclusionsAltogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and well-documented commands.

Indexed as

SoftwareComputational BiologyContig MappingDatabases, FactualHigh-Throughput Nucleotide SequencingMetagenomicsAutomaticMetagenomicsMetatranscriptomicsMicrobial ecologyPipelineVisualization

Identifiers

PMID32795263
PMCPMC7430844

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.