Evidence map›Paper›PMID 25687422›Full record

ArticleSource code for biology and medicine2014

Mega2: validated data-reformatting for linkage and association analyses.

Robert V Baron, Charles Kollar, Nandita Mukhopadhyay, Daniel E Weeks

Abstract read
In one paragraph

Article in Source code for biology and medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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

4 authors.

Robert V BaronDepartment of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261 USA.
Charles KollarDepartment of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261 USA.
Nandita MukhopadhyayDepartment of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA 15261 USA.
Daniel E WeeksDepartment of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261 USA ; Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261 USA.

Funding

Mega2: Manipulation Environment for Genetic AnalysesR01GM076667 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WEEKS, DANIEL E · 2006 to 2018
$3.2M
NIGMS NIH HHS R01 GM076667
6 · The paper itself

Abstract

backgroundIn a typical study of the genetics of a complex human disease, many different analysis programs are used, to test for linkage and association. This requires extensive and careful data reformatting, as many of these analysis programs use differing input formats. Writing scripts to facilitate this can be tedious, time-consuming, and error-prone. To address these issues, the open source Mega2 data reformatting program provides validated and tested data conversions from several commonly-used input formats to many output formats.

resultsMega2, the Manipulation Environment for Genetic Analysis, facilitates the creation of analysis-ready datasets from data gathered as part of a genetic study. It transparently allows users to process genetic data for family-based or case/control studies accurately and efficiently. In addition to data validation checks, Mega2 provides analysis setup capabilities for a broad choice of commonly-used genetic analysis programs. First released in 2000, Mega2 has recently been significantly improved in a number of ways. We have rewritten it in C++ and have reduced its memory requirements. Mega2 now can read input files in LINKAGE, PLINK, and VCF/BCF formats, as well as its own specialized annotated format. It supports conversion to many commonly-used formats including SOLAR, PLINK, Merlin, Mendel, SimWalk2, Cranefoot, IQLS, FBAT, MORGAN, BEAGLE, Eigenstrat, Structure, and PLINK/SEQ. When controlled by a batch file, Mega2 can be used non-interactively in data reformatting pipelines. Support for genetic data from several other species besides humans has been added.

conclusionsBy providing tested and validated data reformatting, Mega2 facilitates more accurate and extensive analyses of genetic data, avoiding the need to write, debug, and maintain one's own custom data reformatting scripts. Mega2 is freely available at https://watson.hgen.pitt.edu/register/.

Indexed as

AssociationData managementHuman GeneticsLinkageSoftware

Identifiers

PMID25687422
PMCPMC4269913

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.