Package 'variantspark'

Extract the importance data frame

Description

This function extracts the importance data frame from the Importance Analysis jobj.

Usage

importance_tbl(importance, name = "importance_tbl")

Arguments

importance	A jobj from the class ImportanceAnalysis, usually the output of vs_importance_analysis().
name	The name to assign to the copied table in Spark.

Examples

## Not run: 
library(sparklyr)
sc <- spark_connect(master = "local")
vsc <- vs_connect(sc)

hipster_vcf <- vs_read_vcf(vsc, 
                           system.file("extdata/hipster.vcf.bz2",
                                       package = "variantspark"))
labels <- vs_read_labels(vsc, 
                         system.file("extdata/hipster_labels.txt",
                                      package = "variantspark"))

importance <- vs_importance_analysis(vsc, hipster_vcf, labels, 10)
importance_tbl(importance)

## End(Not run)

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Display sample names

Description

This function display the first N variant names.

Usage

sample_names(vcf_source, n_samples = NULL)

Arguments

vcf_source	An object with VCFFeatureSource class, usually the output of the vs_read_vcf().
n_samples	The number os samples to display.

Value

spark_jobj, shell_jobj

Examples

## Not run: 
library(sparklyr)

sc <- spark_connect(master = "local")
vsc <- vs_connect(sc)

hipster_vcf <- vs_read_vcf(vsc, 
                           system.file("extdata/hipster.vcf.bz2",
                                       package =  "variantspark"))

sample_names(hipster_vcf, 3)

## End(Not run)

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Creating a variantspark connection

Description

You need to create a variantspark connection to use this extension. To do this, you pass as argument a spark connection that you can create using sparklyr::spark_connect().

Usage

vs_connect(sc)

Arguments

sc	A spark connection.

Value

A variantspark connection

Examples

library(sparklyr)
sc <- spark_connect(master = "spark://HOST:PORT")
connection_is_open(sc)
vsc <- vs_connect(sc)
spark_disconnect(sc)

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Importance Analysis

Description

This function performs an Importance Analysis using random forest algorithm. For more details, please look at here.

Usage

vs_importance_analysis(vsc, vcf_source, labels, n_trees)

Arguments

vsc	A variantspark connection.
vcf_source	An object with VCFFeatureSource class, usually the output of the vs_read_vcf().
labels	An object with CsvLabelSource class, usually the output of the vs_read_labels().
n_trees	The number of trees using in the random forest.

Value

spark_jobj, shell_jobj

Examples

## Not run: 
library(sparklyr)
sc <- spark_connect(master = "local")
vsc <- vs_connect(sc)

hipster_vcf <- vs_read_vcf(vsc, 
                           system.file("extdata/hipster.vcf.bz2",
                                       package =  "variantspark"))

labels <- vs_read_labels(vsc, 
                         system.file("extdata/hipster_labels.txt",
                                      package =  "variantspark"))

vs_importance_analysis(vsc, hipster_vcf, labels, 10)

## End(Not run)

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Reading a CSV file

Description

The vs_read_csv() reads a CSV file format and returns a jobj object from CsvFeatureSource scala class.

Usage

vs_read_csv(vsc, path)

Arguments

vsc	A variantspark connection.
path	The file's path.

Value

spark_jobj, shell_jobj

Examples

## Not run: 
library(sparklyr)

sc <- spark_connect(master = "local")
vsc <- vs_context(sc)

hipster_labels <- vs_read_csv(vsc, 
                              system.file("extdata/hipster_labels.txt",
                                          package = "variantspark"))

hipster_labels 

## End(Not run)

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Reading labels

Description

This function reads only the label column of a CSV file and returns a jobj object from CsvLabelSource scala class.

Usage

vs_read_labels(vsc, path, label = "label")

Arguments

vsc	A variantspark connection.
path	The file's path.
label	A string with the label column name.

Value

spark_jobj, shell_jobj

Examples

## Not run: 
library(sparklyr)

sc <- spark_connect(master = "local")
vsc <- vs_context(sc)

labels <- vs_read_labels(vsc, 
                         system.file("extdata/hipster_labels.txt",
                                      package = "variantspark"))

labels 

## End(Not run)

---

Reading a VCF file

Description

The Variant Call Format (VCF) specifies the format of a text file used in bioinformatics for storing gene sequence variations. The format has been developed with the advent of large-scale genotyping and DNA sequencing projects, such as the 1000 Genomes Project. The vs_read_vcf() reads this format and returns a jobj object from VCFFeatureSource scala class.

Usage

vs_read_vcf(vsc, path)

Arguments

vsc	A variantspark connection.
path	The file's path.

Value

spark_jobj, shell_jobj

Examples

## Not run: 
library(sparklyr)

sc <- spark_connect(master = "local")
vsc <- vs_context(sc)

hipster_vcf <- vs_read_vcf(vsc, 
                           system.file("extdata/hipster.vcf.bz2",
                                       package = "variantspark"))

hipster_vcf 

## End(Not run)

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