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MPAthic: quantitative modeling of sequence-function relationships for massively parallel assays

Ireland, William T. and Kinney, Justin B. (2016) MPAthic: quantitative modeling of sequence-function relationships for massively parallel assays. . (Submitted)

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Massively parallel assays (MPAs) are being rapidly adopted for studying a wide range of DNA, RNA, and protein sequence-function relationships. However, the software available for quantitatively modeling these relationships is severely limited. Here we describe MPAthic, a software package that enables the rapid inference of such models from a variety of MPA datasets. Using both simulated and previously published data, we show that the modeling capabilities of MPAthic greatly improve on those of existing software. In particular, only MPAthic can accurately quantify the strength of epistatic interactions. These capabilities address a major need in the analysis of MPA data.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Material
Ireland, William T.0000-0003-0971-2904
Kinney, Justin B.0000-0003-1897-3778
Additional Information:The copyright holder for this preprint is the author/funder. It is made available under a CC-BY 4.0 International license. bioRxiv preprint first posted online May. 21, 2016. The authors declare that they have no competing interests. Author's contributions: WTI and JBK participated in all aspects of this research. We thank Douglas Fowler for providing preprocessed DMS data from [9]. We also thank Tarjei Mikkelsen for posting the preprocessed MPRA data from [8] on NCBI GEO. WTI was supported by NIH grants DP1 OD000217 and R01 GM085286. The work of JBK was supported by the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory.
Funding AgencyGrant Number
NIHDP1 OD000217
NIHR01 GM085286
Cold Spring Harbor LaboratoryUNSPECIFIED
Record Number:CaltechAUTHORS:20161219-103729326
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:72937
Deposited By: Tony Diaz
Deposited On:19 Dec 2016 19:41
Last Modified:09 Mar 2020 13:18

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