Evidence map›Paper›PMID 34544908›Full record

ArticleJournal of biosciences2021

GAMUT: A genomics big data management tool.

E P Ramakrishnan, Saurabh Gupta, Renu Gadhari, Neeraj Bharti, Sandeep Malviya, Sunitha Manjari Kasibhatla, Jan Kim, Rajendra Joshi

Abstract read
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In one paragraph

Article in Journal of biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

E P RamakrishnanHigh Performance Computing-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Innovation Park, Panchavati, Pashan, Pune 411008, India.
Saurabh Gupta
Renu Gadhari
Neeraj Bharti
Sandeep Malviya
Sunitha Manjari Kasibhatla
Jan Kim
Rajendra Joshi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient analysis of Single Nucleotide Polymorphisms (SNPs) across genomic samples enable in deciphering the relationship between genotype and phenotype. The core principle behind SNP comparison is to arrive at a probable list of variants that can differentiate two sets of data (populations). Such SNPs have direct applications in array design, genotype imputation and in cataloging of variants in regions of interest. We have developed GAMUT (Genomics bigdAta Management Tool), a big data-based solution for efficient run-time comparison of SNPs across large datasets based on partition of samples belonging to different populations taking into account user-defined splits. The tool is based on client-server architecture with MongoDB at the back-end and JSF with PrimeFaces as the front-end. It is readily deployable on wild-fly server as well as a docker container. Spark-based parallel data uploader enables optimal loading times. GAMUT enables dynamic querying of the large datasets consisting of multiple samples using text-based, chromosome position-based as well as gene-name based options. Various charting options like bar and pie charts along with tabular formats are available to ease the analysis of the queried data. The resultant data pertaining to comparison of genomewide SNPs can also be downloaded in different formats like text, html, json for further stand-alone analysis. GAMUT is available for download at: https://github.com/bioinformatics-cdac/gamut.

Indexed as

Big DataDatabases, FactualData ManagementGenomicsGenotypeHumansPolymorphism, Single NucleotideSoftware

Identifiers

PMID34544908

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.