Evidence map›Paper›PMID 31757212›Full record

ArticleBMC bioinformatics2019

TACITuS: transcriptomic data collector, integrator, and selector on big data platform.

Salvatore Alaimo, Antonio Di Maria, Dennis Shasha, Alfredo Ferro, Alfredo Pulvirenti

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. 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. 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

5 authors.

Salvatore AlaimoDepartment of Clinical and Experimental Medicine, University of Catania, c/o Dipartimento di Matematica e Informatica, Viale A. Doria 6, Catania, 95125, Italy. alaimos@dmi.unict.it.ORCID http://orcid.org/0000-0003-4825-7617
Antonio Di MariaDepartment of Clinical and Experimental Medicine, University of Catania, c/o Dipartimento di Matematica e Informatica, Viale A. Doria 6, Catania, 95125, Italy.
Dennis ShashaCourant Institute of Mathematical Science, New York University, 251 Mercer St, New York, 10012, USA.
Alfredo FerroDepartment of Clinical and Experimental Medicine, University of Catania, c/o Dipartimento di Matematica e Informatica, Viale A. Doria 6, Catania, 95125, Italy.
Alfredo PulvirentiDepartment of Clinical and Experimental Medicine, University of Catania, c/o Dipartimento di Matematica e Informatica, Viale A. Doria 6, Catania, 95125, Italy.

Funding

Ministero dell'Istruzione, dell'Università e della Ricerca FFABRNational Science Foundation IOS-0922738National Science Foundation IOS-1339362National Science Foundation MCB-0929339National Science Foundation MCB-1158273National Science Foundation MCB-1355462National Science Foundation MCB-1412232Università di Catania Marcatori molecolari e clinico-strumentali precoci, nelle patologie metaboliche e cronico-degenerative
6 · The paper itself

Abstract

backgroundSeveral large public repositories of microarray datasets and RNA-seq data are available. Two prominent examples include ArrayExpress and NCBI GEO. Unfortunately, there is no easy way to import and manipulate data from such resources, because the data is stored in large files, requiring large bandwidth to download and special purpose data manipulation tools to extract subsets relevant for the specific analysis.

resultsTACITuS is a web-based system that supports rapid query access to high-throughput microarray and NGS repositories. The system is equipped with modules capable of managing large files, storing them in a cloud environment and extracting subsets of data in an easy and efficient way. The system also supports the ability to import data into Galaxy for further analysis.

conclusionsTACITuS automates most of the pre-processing needed to analyze high-throughput microarray and NGS data from large publicly-available repositories. The system implements several modules to manage large files in an easy and efficient way. Furthermore, it is capable deal with Galaxy environment allowing users to analyze data through a user-friendly interface.

Indexed as

Big DataData CollectionSoftwareCell Line, TumorDatabases, GeneticHumansTranscriptomeUser-Computer InterfaceCloud storage and managementGalaxyRNA-Seq

Identifiers

PMID31757212
PMCPMC6873396

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.