Description Usage Arguments Details Value Examples
Find peak genes (spatially upregulated genes) in a SummarizedExperiment object.
1 2 3 4 5 6 7 8 | findPeakGene(
object,
threshold = 1,
length = 4,
matrix = "scaled",
nperm = 1e+05,
method = "BH"
)
|
object |
A |
threshold |
Integer, only scaled read counts bigger than |
length |
Integer, scaled read counts bigger than |
matrix |
Character, must be one of |
nperm |
Integer, number of random permutations to calculate p values. Set it to 0 if you are not interested in p values. |
method |
Character, the method to adjust p values for multiple comparisons, must be one of |
Peak genes are selected based on scaled read counts. As scaled read counts are Z scores, suggested threshold are [1,3].
Smaller threshold and length makes the function detect more peak genes, and vice versa.
P values are calculated by approximate permutation tests. For a given threshold and length, the scaled read counts of each gene is randomly permutated for nperm times. The p value is defined as the ratio of permutations containing peaks.
In order to speed up permutation process, genes whose expression exceeds threshold in same number of sections have same p values.
To be specific, only one of these genes will be used to calculate a p value by permutation, and other genes are assigned this p value.
A data.frame with peak genes as rows. It has following columns:
gene : Character, peak gene names.
start : Numeric, the start index of peak.
end : Numeric, the end index of peak.
center : Numeric, the middle index of peak. If the length of the peak is even, center is defined as the left-middle index.
p : Numeric, p values.
p.adj : Numeric, adjusted p values.
1 2 3 4 5 6 7 8 9 10 11 12 13 | data(zh.data)
zh <- createTomo(zh.data)
peak_genes <- findPeakGene(zh)
head(peak_genes)
# Increase threshold so that less peak genes will be found.
peak_genes <- findPeakGene(zh, threshold=1.5)
# Increase peak length so that less peak genes will be found.
peak_genes <- findPeakGene(zh, length=5)
# Set nperm to 0 so that p values will not be calculated. This will save running time.
peak_genes <- findPeakGene(zh, nperm=0)
|
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