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Function aCGH.process [aCGH v1.50.0]
keywords
file
title
Process data in aCGH object
description
This function takes object of class aCGH, and filters clones based on their mapping information and proportion missing. It also average duplicated clones and reports quality statistic.
Function aCGH.read.Sprocs [aCGH v1.50.0]
keywords
file
title
Create object of class "aCGH" from Sproc files
description
This function reads in two-channel Array Comparative Genomic Hybridization Sproc files, flags them for bad quality and missing data, and creates object of class aCGH.
Function readImaGeneHeader [limma v3.28.14]
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file
title
Read ImaGene Header Information
description
Read the header information from an ImaGene image analysis output file. This function is used internally by read.maimages and is not usually called directly by users.
Function HarshComp [Harshlight v1.44.0]
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file
title
a blemish detection program for microarray chips: extended and compact defects only
description
Harshlight automatically detects and masks blemishes in microarray chips of class AffyBatch
Function HarshExt [Harshlight v1.44.0]
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file
title
a blemish detection program for microarray chips: extended defects only
description
Harshlight automatically detects and masks blemishes in microarray chips of class AffyBatch
Function Harshlight [Harshlight v1.44.0]
keywords
file
title
a blemish detection program for microarray chips: extended, diffuse, and compact defects
description
Harshlight automatically detects and masks blemishes in microarray chips of class AffyBatch
Function getCoExpGeneofLncs [LncPriCNet v1.0]
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file
title
Get Co-expressed Genes of LncRNAs
description
Get co-expressed genes of one or some lncRNAs based on the multi-omics network.
Function getDiseaseInf [LncPriCNet v1.0]
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file
title
Get All Disease Information based on phenotype id (OMIM Id) Provided by LncPriCNet Package
description
Get all disease information provided by LncPriCNet package by OMIMID. This function will provide you known disease genes and lncRNAs corresponding phenotype.
Function getTopDiseaseLncRNAs [LncPriCNet v1.0]
keywords
file
title
Get the Disease Risk LncRNAs
description
prioritize the disease candidate lncRNAs by integrated multi-omics information.
Function RNetCDF [RNetCDF v1.9-1]
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file
title
R Interface to NetCDF Datasets
description
This package provides an interface to Unidata's NetCDF library functions (version 3) and furthermore access to Unidata's UDUNITS calendar conversions. The routines and the documentation follow the NetCDF and UDUNITS C interface, so the corresponding manuals can be consulted for more detailed information. NetCDF is an abstraction that supports a view of data as a collection of self-describing, portable objects that can be accessed through a simple interface. Array values may be accessed directly, without knowing details of how the data are stored. Auxiliary information about the data, such as what units are used, may be stored with the data. Generic utilities and application programs can access NetCDF datasets and transform, combine, analyze, or display specified fields of the data. The external types supported by the NetCDF interface are: NC_CHAR 8-bit characters intended for representing text. NC_BYTE 8-bit signed or unsigned integers. NC_SHORT 16-bit signed integers. NC_INT 32-bit signed integers. NC_FLOAT 32-bit IEEE floating-point. NC_DOUBLE 64-bit IEEE floating-point. These types are called ``external'', because they correspond to the portable external representation for NetCDF data. When a program reads external NetCDF data into an internal variable, the data is converted, if necessary, into the specified internal type. Similarly, if you write internal data into a NetCDF variable, this may cause it to be converted to a different external type, if the external type for the NetCDF variable differs from the internal type. First versions of the R and C code of this package were based on the netCDF package by Thomas Lumley and the ncdf package by David Pierce. Milton Woods added some enhancements of the NetCDF library version 3.6. A high-level interface based on this library is the ncvar package by Juerg Schmidli. It simplifies the handling of datasets which contain lots of metadata. Different metadata conventions are supported including the CF metadata conventions used by the climate modeling and forecasting community.