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HLA-DQ and RBFOX1 as susceptibility genes for an outbreak of hydrolyzed wheat allergy.

Emiko Noguchi | Masato Akiyama | Akiko Yagami | Tomomitsu Hirota | Yukinori Okada | Zenichiro Kato | Reiko Kishikawa | Yuma Fukutomi | Michihiro Hide | Eishin Morita | Michiko Aihara | Makiko Hiragun | Yuko Chinuki | Takahiro Okabe | Akiko Ito | Atsuko Adachi | Atsushi Fukunaga | Yumiko Kubota | Toshiyuki Aoki | Youko Aoki | Kazue Nishioka | Tetsuya Adachi | Nobuo Kanazawa | Hitoshi Miyazawa | Hiroyuki Sakai | Takehito Kozuka | Hideo Kitamura | Hideo Hashizume | Chiharu Kanegane | Koji Masuda | Kumiya Sugiyama | Reiko Tokuda | Junichi Furuta | Ikkou Higashimoto | Atsuko Kato | Mariko Seishima | Akihiko Tajiri | Atsuko Tomura | Hiroko Taniguchi | Hiroto Kojima | Hidenori Tanaka | Aiko Sakai | Wataru Morii | Masashi Nakamura | Yoichiro Kamatani | Atsushi Takahashi | Michiaki Kubo | Mayumi Tamari | Hirohisa Saito | Kayoko Matsunaga
The Journal of allergy and clinical immunology | 2019

Food allergy is a growing health problem worldwide because of its increasing prevalence, life-threatening potential, and shortage of effective preventive treatments. In an outbreak of wheat allergy in Japan, thousands of patients had allergic reactions to wheat after using soap containing hydrolyzed wheat protein (HWP).

Pubmed ID: 31301374

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


1000 Genomes Project and AWS (tool)

RRID:SCR_008801

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

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ARLEQUIN (tool)

RRID:SCR_009051

An exploratory population genetics software environment able to handle large samples of molecular data (RFLPs, DNA sequences, microsatellites), while retaining the capacity of analyzing conventional genetic data (standard multi-locus data or mere allele frequency data). (entry from Genetic Analysis Software)

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