tsum_test: Generate T sum statistics and p-values from simulation.

Description Usage Arguments Value References See Also Examples

View source: R/tsum_test.R

Description

When applied to an exstra_score object, T sum statistics are calculated as described in Tankard et al. May also be applied on a pre-existing exstra_tsum that will regenerate the values.

Usage

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tsum_test(strscore, trim = 0.15, min.quant = 0.5, give.pvalue = TRUE,
  B = 9999, correction = c("bf", "locus", "uncorrected"), alpha = 0.05,
  parallel = FALSE, cluster_n = NULL, cluster = NULL)

Arguments

strscore

An exstra_score object.

trim

Trim this proportion of data points at each quantile level (rounded up). Must be at least 0 and less than 0.5, but values close to 0.5 may remove all samples and hence result in an error.

min.quant

Only quantiles above this value are used in constructing the statistic.

give.pvalue

Whether to calculate the p-value. As this can be slow it can be useful to turn off if only the t sum statistics are required.

B

Number of simulations in calculating null distributions. The denominator will be B + 1, hence values of B = 10^i - 1 will result in p-values that are decimal fractions.

correction

Correction method of p_value() function.

alpha

Signficance level of p_value() function.

parallel

Use the parallel package when simulating the distribution, creating the required cluster. If cluster is specified then this option makes no difference.

cluster_n

If parallel is TRUE, then the number of nodes in the cluster is automatically set as 1 less than those available on your machine. (but never less than 1). This option allows manual setting of the number of nodes, either less to free up other resources, or more to maximize available resources. If cluster is specified then this option makes no difference.

cluster

A cluster object from the parallel package. Use if you wish to set up the cluster yourself or reuse an existing cluster.

Value

An exstra_tsum object with T statistics and p-values (if calculated).

References

Rick M. Tankard, Martin B. Delatycki, Paul J. Lockhart, Melanie Bahlo. Detecting known repeat expansions with standard protocol next generation sequencing, towards developing a single screening test for neurological repeat expansion disorders. bioRxiv 157792; doi: https://doi.org/10.1101/157792

See Also

tsum_p_value_summary

Examples

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exp_test <- tsum_test(exstra_wgs_pcr_2[c("HD", "SCA6")], B = 50)
exp_test

## Not run: 
exp_test_parallel <- tsum_test(exstra_wgs_pcr_2[c("HD", "SCA6")], parallel = TRUE, B = 999)
exp_test_parallel

## End(Not run)

bahlolab/exSTRa documentation built on Nov. 8, 2017, 10:52 a.m.