Result for 088DDE091E21052E2DE4A2B3AE7BA5C81D4EE248

Query result

Key Value
FileName./usr/lib64/R/library/PCRedux/DESCRIPTION
FileSize2903
MD54E460D44B88A2C1F4719E7E6A26CE950
SHA-1088DDE091E21052E2DE4A2B3AE7BA5C81D4EE248
SHA-256038A6130FFD006022DE25E66CA632EFB5CA9BA0E6353332255CA58AC00BAF69C
SSDEEP48:b4hffdBnKcqHx9w13uC0vwQacv91Z1aUKKdsnIsKpx:bC3dBKcqHx9w1uC03vjZ1aSmnIvH
TLSHT1F151C92264A11151B68760E625BB7A00755F710F2AD010BCBAFEC5A03F0CABD2EFA594
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5D8120A9F3E2C150E9D7529370A551324
PackageArchx86_64
PackageDescriptionExtracts features from amplification curve data of quantitative Polymerase Chain Reactions (qPCR) (Pabinger S. et al. (2014) <doi:10.1016/j.bdq.2014.08.002>) for machine learning purposes. Helper functions prepare the amplification curve data for processing as functional data (e.g., Hausdorff distance) or enable the plotting of amplification curve classes (negative, ambiguous, positive). The hookreg() and hookregNL() functions (Burdukiewicz M. et al. (2018) <doi:10.1016/j.bdq.2018.08.001>) can be used to predict amplification curves with an hook effect-like curvature. The pcrfit_single() function can be used to extract features from an amplification curve.
PackageNameR-PCRedux
PackageReleaselp154.10.1
PackageVersion1.1
SHA-1758E00D96BD00B6C60DD01DA15629E21FBA35C4A
SHA-2565FE58842C0BB70685411242157EAD3664C89A8D8B5B8FC57BB14D18F01D67BF7