InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]

As somatic next-generation sequencing gene panel analysis in advanced cancer patients is becoming more routine, oncologists are frequently presented with reports containing lists of genes with increased copy number. Distinguishing which of these amplified genes, if any, might be driving tumor growth...

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Main Author:	Paraic A. Kenny
Format:	Article
Language:	English
Published:	F1000 Research Ltd 2019-09-01
Series:	F1000Research
Online Access:	https://f1000research.com/articles/8-807/v3

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spelling	doaj-c30bf10a2d29449c817d549a78ac26f92020-11-25T02:31:39ZengF1000 Research LtdF1000Research2046-14022019-09-01810.12688/f1000research.19541.322814InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]Paraic A. Kenny0Kabara Cancer Research Institute, Gundersen Medical Foundation, La Crosse, WI, 54601, USAAs somatic next-generation sequencing gene panel analysis in advanced cancer patients is becoming more routine, oncologists are frequently presented with reports containing lists of genes with increased copy number. Distinguishing which of these amplified genes, if any, might be driving tumor growth and might thus be worth considering targeting can be challenging. One particular issue is the frequent absence of genomic contextual information in clinical reports, making it very challenging to determine which reported genes might be co-amplified and how large any such amplicons might be. We describe a straightforward Python web app, InferAMP, into which healthcare professionals may enter lists of amplified genes from clinical reports. The tool reports (1) the likely size of amplified genomic regions, (2) which reported genes are co-amplified and (3) which other cancer-relevant genes that were not evaluated in the assay may also be co-amplified in the specimen. The tool is accessible for web queries at http://inferamp.org.https://f1000research.com/articles/8-807/v3
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Paraic A. Kenny
spellingShingle	Paraic A. Kenny InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved] F1000Research
author_facet	Paraic A. Kenny
author_sort	Paraic A. Kenny
title	InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]
title_short	InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]
title_full	InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]
title_fullStr	InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]
title_full_unstemmed	InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]
title_sort	inferamp, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]
publisher	F1000 Research Ltd
series	F1000Research
issn	2046-1402
publishDate	2019-09-01
description	As somatic next-generation sequencing gene panel analysis in advanced cancer patients is becoming more routine, oncologists are frequently presented with reports containing lists of genes with increased copy number. Distinguishing which of these amplified genes, if any, might be driving tumor growth and might thus be worth considering targeting can be challenging. One particular issue is the frequent absence of genomic contextual information in clinical reports, making it very challenging to determine which reported genes might be co-amplified and how large any such amplicons might be. We describe a straightforward Python web app, InferAMP, into which healthcare professionals may enter lists of amplified genes from clinical reports. The tool reports (1) the likely size of amplified genomic regions, (2) which reported genes are co-amplified and (3) which other cancer-relevant genes that were not evaluated in the assay may also be co-amplified in the specimen. The tool is accessible for web queries at http://inferamp.org.
url	https://f1000research.com/articles/8-807/v3
work_keys_str_mv	AT paraicakenny inferampapythonwebappforcopynumberinferencefromdiscretegenelevelamplificationsignalsnotedinclinicaltumorprofilingreportsversion3peerreview2approved
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InferAMP, a python web app for copy number inference from discrete gene-level amplification signals noted in clinical tumor profiling reports [version 3; peer review: 2 approved]

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