DEtype: DEtype: Classifying differentially expressed genes from...

In miaozhun/DEsingle: DEsingle for detecting three types of differential expression in single-cell RNA-seq data

DEtype: Classifying differentially expressed genes from DEsingle

Description

This function is used to classify the differentially expressed genes of single-cell RNA-seq (scRNA-seq) data found by DEsingle. It takes the output data frame from DEsingle as input.

Usage

DEtype(results, threshold)

Arguments

results	A output data frame from DEsingle, which contains the unclassified differential expression analysis results.
threshold	A number of (0,1) to specify the threshold of FDR.

Value

A data frame containing the differential expression (DE) analysis results and DE gene types and states.

• theta_1, theta_2, mu_1, mu_2, size_1, size_2, prob_1, prob_2: MLE of the zero-inflated negative binomial distribution's parameters of group 1 and group 2.

• total_mean_1, total_mean_2: Mean of read counts of group 1 and group 2.

• foldChange: total_mean_1/total_mean_2.

• norm_total_mean_1, norm_total_mean_2: Mean of normalized read counts of group 1 and group 2.

• norm_foldChange: norm_total_mean_1/norm_total_mean_2.

• chi2LR1: Chi-square statistic for hypothesis testing of H0.

• pvalue_LR2: P value of hypothesis testing of H20 (Used to determine the type of a DE gene).

• pvalue_LR3: P value of hypothesis testing of H30 (Used to determine the type of a DE gene).

• FDR_LR2: Adjusted P value of pvalue_LR2 using Benjamini & Hochberg's method (Used to determine the type of a DE gene).

• FDR_LR3: Adjusted P value of pvalue_LR3 using Benjamini & Hochberg's method (Used to determine the type of a DE gene).

• pvalue: P value of hypothesis testing of H0 (Used to determine whether a gene is a DE gene).

• pvalue.adj.FDR: Adjusted P value of H0's pvalue using Benjamini & Hochberg's method (Used to determine whether a gene is a DE gene).

• Remark: Record of abnormal program information.

• Type: Types of DE genes. DEs represents different expression status; DEa represents differential expression abundance; DEg represents general differential expression.

• State: State of DE genes, up represents up-regulated; down represents down-regulated.

Author(s)

Zhun Miao.

See Also

DEsingle, for the detection of differentially expressed genes from scRNA-seq data.

TestData, a test dataset for DEsingle.

Examples

# Load test data for DEsingle
data(TestData)

# Specifying the two groups to be compared
# The sample number in group 1 and group 2 is 50 and 100 respectively
group <- factor(c(rep(1,50), rep(2,100)))

# Detecting the differentially expressed genes
results <- DEsingle(counts = counts, group = group)

# Dividing the differentially expressed genes into 3 categories
results.classified <- DEtype(results = results, threshold = 0.05)

miaozhun/DEsingle documentation built on Jan. 25, 2023, 4:27 p.m.