Description Usage Arguments Value Author(s) See Also Examples

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.

1 | ```
DEtype(results, threshold)
``` |

`results` |
A output data frame from |

`threshold` |
A number of (0,1) to specify the threshold of FDR. |

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.

Zhun Miao.

`DEsingle`

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

`TestData`

, a test dataset for DEsingle.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
# 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)
``` |

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