Perform statistical analyses
Usage
diffAnalyses(
data,
groups = NULL,
analyses = c("wilcoxRankSum", "ttest", "kruskal", "levene", "fligner"),
pvalueAdjust = "BH",
geneExpr = NULL,
inputID = "sparklineInput"
)Arguments
- data
Data frame or matrix: gene expression or alternative splicing quantification
- groups
Named list of characters (containing elements belonging to each group) or character vector (containing the group of each individual sample); if
NULL, sample types are used instead when available, e.g. normal, tumour and metastasis- analyses
Character: statistical tests to perform (see Details)
- pvalueAdjust
Character: method used to adjust p-values (see Details)
- geneExpr
Character: name of the gene expression dataset (only required for density sparklines available in the interactive mode)
- inputID
Character: identifier of input to get attributes of clicked event (Shiny only)
Details
The following statistical analyses may be performed simultaneously via the
analysis argument:
ttest- Unpaired t-test (2 groups)wilcoxRankSum- Wilcoxon Rank Sum test (2 groups)kruskal- Kruskal test (2 or more groups)levene- Levene's test (2 or more groups)fligner- Fligner-Killeen test (2 or more groups)density- Sample distribution per group (only usable through the visual interface)
The following p-value adjustment methods are supported via the
pvalueAdjust argument:
none: do not adjust p-valuesBH: Benjamini-Hochberg's method (false discovery rate)BY: Benjamini-Yekutieli's method (false discovery rate)bonferroni: Bonferroni correction (family-wise error rate)holm: Holm's method (family-wise error rate)hochberg: Hochberg's method (family-wise error rate)hommel: Hommel's method (family-wise error rate)
See also
Other functions to perform and plot differential analyses:
plotDistribution()
Examples
# Calculate PSI for skipped exon (SE) and mutually exclusive (MXE) events
eventType <- c("SE", "MXE")
annot <- readFile("ex_splicing_annotation.RDS")
junctionQuant <- readFile("ex_junctionQuant.RDS")
psi <- quantifySplicing(annot, junctionQuant, eventType=c("SE", "MXE"))
#> Using 3 of 3 events (100%) whose junctions are present in junction quantification data...
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#> Using 3 of 3 events (100%) whose junctions are present in junction quantification data...
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group <- c(rep("Normal", 3), rep("Tumour", 3))
diffAnalyses(psi, group)
#>
#> Time difference of 0.0211 secs
#>
#> Time difference of 0.00564 secs
#>
#> Time difference of 0.000284 secs
#>
#> Time difference of 0.000922 secs
#> Event type Chromosome Strand
#> SE_1_+_32_35_37_38_ACTN1 Skipped exon (SE) 1 +
#> MXE_1_+_32_35_37_38_40_42_ACTN1 Mutually exclusive exon (MXE) 1 +
#> SE_2_+_32_35_37_38_ALDOA Skipped exon (SE) 2 +
#> SE_3_+_32_35_37_38_ANXA6 Skipped exon (SE) 3 +
#> MXE_2_+_32_35_37_38_40_42_ALDOA Mutually exclusive exon (MXE) 2 +
#> MXE_3_+_32_35_37_38_40_42_ANXA6 Mutually exclusive exon (MXE) 3 +
#> Gene Survival by PSI cutoff Optimal PSI cutoff
#> SE_1_+_32_35_37_38_ACTN1 ACTN1 <NA> <NA>
#> MXE_1_+_32_35_37_38_40_42_ACTN1 ACTN1 <NA> <NA>
#> SE_2_+_32_35_37_38_ALDOA ALDOA <NA> <NA>
#> SE_3_+_32_35_37_38_ANXA6 ANXA6 <NA> <NA>
#> MXE_2_+_32_35_37_38_40_42_ALDOA ALDOA <NA> <NA>
#> MXE_3_+_32_35_37_38_40_42_ANXA6 ANXA6 <NA> <NA>
#> Log-rank p-value Samples (Normal)
#> SE_1_+_32_35_37_38_ACTN1 <NA> 3
#> MXE_1_+_32_35_37_38_40_42_ACTN1 <NA> 3
#> SE_2_+_32_35_37_38_ALDOA <NA> 3
#> SE_3_+_32_35_37_38_ANXA6 <NA> 3
#> MXE_2_+_32_35_37_38_40_42_ALDOA <NA> 3
#> MXE_3_+_32_35_37_38_40_42_ANXA6 <NA> 3
#> Samples (Tumour) Wilcoxon statistic
#> SE_1_+_32_35_37_38_ACTN1 3 4.5
#> MXE_1_+_32_35_37_38_40_42_ACTN1 3 4.5
#> SE_2_+_32_35_37_38_ALDOA 3 6.0
#> SE_3_+_32_35_37_38_ANXA6 3 4.0
#> MXE_2_+_32_35_37_38_40_42_ALDOA 3 8.0
#> MXE_3_+_32_35_37_38_40_42_ANXA6 3 2.0
#> Wilcoxon p-value Wilcoxon p-value (BH adjusted)
#> SE_1_+_32_35_37_38_ACTN1 NaN NaN
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN NaN
#> SE_2_+_32_35_37_38_ALDOA 0.7 0.9333333
#> SE_3_+_32_35_37_38_ANXA6 1.0 1.0000000
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.2 0.8000000
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.4 0.8000000
#> Wilcoxon null value Wilcoxon alternative
#> SE_1_+_32_35_37_38_ACTN1 0 two.sided
#> MXE_1_+_32_35_37_38_40_42_ACTN1 0 two.sided
#> SE_2_+_32_35_37_38_ALDOA 0 two.sided
#> SE_3_+_32_35_37_38_ANXA6 0 two.sided
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0 two.sided
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0 two.sided
#> Wilcoxon method
#> SE_1_+_32_35_37_38_ACTN1 Wilcoxon rank sum test with continuity correction
#> MXE_1_+_32_35_37_38_40_42_ACTN1 Wilcoxon rank sum test with continuity correction
#> SE_2_+_32_35_37_38_ALDOA Wilcoxon rank sum exact test
#> SE_3_+_32_35_37_38_ANXA6 Wilcoxon rank sum exact test
#> MXE_2_+_32_35_37_38_40_42_ALDOA Wilcoxon rank sum exact test
#> MXE_3_+_32_35_37_38_40_42_ANXA6 Wilcoxon rank sum exact test
#> Wilcoxon data name
#> SE_1_+_32_35_37_38_ACTN1 vector[typeOne] and vector[!typeOne]
#> MXE_1_+_32_35_37_38_40_42_ACTN1 vector[typeOne] and vector[!typeOne]
#> SE_2_+_32_35_37_38_ALDOA vector[typeOne] and vector[!typeOne]
#> SE_3_+_32_35_37_38_ANXA6 vector[typeOne] and vector[!typeOne]
#> MXE_2_+_32_35_37_38_40_42_ALDOA vector[typeOne] and vector[!typeOne]
#> MXE_3_+_32_35_37_38_40_42_ANXA6 vector[typeOne] and vector[!typeOne]
#> Kruskal statistic Kruskal parameter
#> SE_1_+_32_35_37_38_ACTN1 NaN 1
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN 1
#> SE_2_+_32_35_37_38_ALDOA 0.42857143 1
#> SE_3_+_32_35_37_38_ANXA6 0.04761905 1
#> MXE_2_+_32_35_37_38_40_42_ALDOA 2.33333333 1
#> MXE_3_+_32_35_37_38_40_42_ANXA6 1.19047619 1
#> Kruskal p-value Kruskal p-value (BH adjusted)
#> SE_1_+_32_35_37_38_ACTN1 NaN NaN
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN NaN
#> SE_2_+_32_35_37_38_ALDOA 0.5126908 0.6835877
#> SE_3_+_32_35_37_38_ANXA6 0.8272593 0.8272593
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.1266305 0.5065218
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.2752335 0.5504670
#> Kruskal method Kruskal data name
#> SE_1_+_32_35_37_38_ACTN1 Kruskal-Wallis rank sum test vector and group
#> MXE_1_+_32_35_37_38_40_42_ACTN1 Kruskal-Wallis rank sum test vector and group
#> SE_2_+_32_35_37_38_ALDOA Kruskal-Wallis rank sum test vector and group
#> SE_3_+_32_35_37_38_ANXA6 Kruskal-Wallis rank sum test vector and group
#> MXE_2_+_32_35_37_38_40_42_ALDOA Kruskal-Wallis rank sum test vector and group
#> MXE_3_+_32_35_37_38_40_42_ANXA6 Kruskal-Wallis rank sum test vector and group
#> Levene statistic Levene p-value
#> SE_1_+_32_35_37_38_ACTN1 NaN NaN
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN NaN
#> SE_2_+_32_35_37_38_ALDOA 1.534423 0.2831735
#> SE_3_+_32_35_37_38_ANXA6 1.898555 0.2403023
#> MXE_2_+_32_35_37_38_40_42_ALDOA 1.102360 0.3529948
#> MXE_3_+_32_35_37_38_40_42_ANXA6 1.453025 0.2944743
#> Levene p-value (BH adjusted) Levene data name
#> SE_1_+_32_35_37_38_ACTN1 NaN vector and group
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN vector and group
#> SE_2_+_32_35_37_38_ALDOA 0.3529948 vector and group
#> SE_3_+_32_35_37_38_ANXA6 0.3529948 vector and group
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.3529948 vector and group
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.3529948 vector and group
#> Levene method
#> SE_1_+_32_35_37_38_ACTN1 Levene's test (using the median)
#> MXE_1_+_32_35_37_38_40_42_ACTN1 Levene's test (using the median)
#> SE_2_+_32_35_37_38_ALDOA Levene's test (using the median)
#> SE_3_+_32_35_37_38_ANXA6 Levene's test (using the median)
#> MXE_2_+_32_35_37_38_40_42_ALDOA Levene's test (using the median)
#> MXE_3_+_32_35_37_38_40_42_ANXA6 Levene's test (using the median)
#> Fligner-Killeen statistic
#> SE_1_+_32_35_37_38_ACTN1 NaN
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN
#> SE_2_+_32_35_37_38_ALDOA 1.042057
#> SE_3_+_32_35_37_38_ANXA6 1.042057
#> MXE_2_+_32_35_37_38_40_42_ALDOA 1.042057
#> MXE_3_+_32_35_37_38_40_42_ANXA6 1.042057
#> Fligner-Killeen parameter
#> SE_1_+_32_35_37_38_ACTN1 1
#> MXE_1_+_32_35_37_38_40_42_ACTN1 1
#> SE_2_+_32_35_37_38_ALDOA 1
#> SE_3_+_32_35_37_38_ANXA6 1
#> MXE_2_+_32_35_37_38_40_42_ALDOA 1
#> MXE_3_+_32_35_37_38_40_42_ANXA6 1
#> Fligner-Killeen p-value
#> SE_1_+_32_35_37_38_ACTN1 NaN
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN
#> SE_2_+_32_35_37_38_ALDOA 0.3073435
#> SE_3_+_32_35_37_38_ANXA6 0.3073435
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.3073435
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.3073435
#> Fligner-Killeen p-value (BH adjusted)
#> SE_1_+_32_35_37_38_ACTN1 NaN
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NaN
#> SE_2_+_32_35_37_38_ALDOA 0.3073435
#> SE_3_+_32_35_37_38_ANXA6 0.3073435
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.3073435
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.3073435
#> Fligner-Killeen method
#> SE_1_+_32_35_37_38_ACTN1 Fligner-Killeen test of homogeneity of variances
#> MXE_1_+_32_35_37_38_40_42_ACTN1 Fligner-Killeen test of homogeneity of variances
#> SE_2_+_32_35_37_38_ALDOA Fligner-Killeen test of homogeneity of variances
#> SE_3_+_32_35_37_38_ANXA6 Fligner-Killeen test of homogeneity of variances
#> MXE_2_+_32_35_37_38_40_42_ALDOA Fligner-Killeen test of homogeneity of variances
#> MXE_3_+_32_35_37_38_40_42_ANXA6 Fligner-Killeen test of homogeneity of variances
#> Fligner-Killeen data name Variance (Normal)
#> SE_1_+_32_35_37_38_ACTN1 vector and group 0.000000000
#> MXE_1_+_32_35_37_38_40_42_ACTN1 vector and group 0.000000000
#> SE_2_+_32_35_37_38_ALDOA vector and group 0.026663118
#> SE_3_+_32_35_37_38_ANXA6 vector and group 0.005240524
#> MXE_2_+_32_35_37_38_40_42_ALDOA vector and group 0.019685695
#> MXE_3_+_32_35_37_38_40_42_ANXA6 vector and group 0.022583581
#> Variance (Tumour) Median (Normal)
#> SE_1_+_32_35_37_38_ACTN1 0.0000000000 0.5000000
#> MXE_1_+_32_35_37_38_40_42_ACTN1 0.0000000000 0.5000000
#> SE_2_+_32_35_37_38_ALDOA 0.0027119499 0.7402597
#> SE_3_+_32_35_37_38_ANXA6 0.0003158887 0.4255319
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.0035641399 0.7500000
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.0027577471 0.2597403
#> Median (Tumour) T-test statistic
#> SE_1_+_32_35_37_38_ACTN1 0.5000000 NA
#> MXE_1_+_32_35_37_38_40_42_ACTN1 0.5000000 NA
#> SE_2_+_32_35_37_38_ALDOA 0.6037736 1.04878918
#> SE_3_+_32_35_37_38_ANXA6 0.4418605 -0.02602006
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.5918367 1.73393229
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.3846154 -1.45806393
#> T-test parameter T-test p-value
#> SE_1_+_32_35_37_38_ACTN1 NA NA
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NA NA
#> SE_2_+_32_35_37_38_ALDOA 2.402681 0.3881661
#> SE_3_+_32_35_37_38_ANXA6 2.240239 0.9813765
#> MXE_2_+_32_35_37_38_40_42_ALDOA 2.701223 0.1913725
#> MXE_3_+_32_35_37_38_40_42_ANXA6 2.481275 0.2586925
#> T-test p-value (BH adjusted) T-test conf int1
#> SE_1_+_32_35_37_38_ACTN1 NA NA
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NA NA
#> SE_2_+_32_35_37_38_ALDOA 0.5175548 -0.2604062
#> SE_3_+_32_35_37_38_ANXA6 0.9813765 -0.1685048
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.5173850 -0.1458915
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.5173850 -0.4643286
#> T-test conf int2 T-test estimate1
#> SE_1_+_32_35_37_38_ACTN1 NA NA
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NA NA
#> SE_2_+_32_35_37_38_ALDOA 0.4679678 0.7217532
#> SE_3_+_32_35_37_38_ANXA6 0.1662652 0.4353827
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.4511807 0.7434609
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.1963126 0.2671886
#> T-test estimate2 T-test null value
#> SE_1_+_32_35_37_38_ACTN1 NA NA
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NA NA
#> SE_2_+_32_35_37_38_ALDOA 0.6179724 0
#> SE_3_+_32_35_37_38_ANXA6 0.4365025 0
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.5908163 0
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.4011966 0
#> T-test stderr T-test alternative
#> SE_1_+_32_35_37_38_ACTN1 NA <NA>
#> MXE_1_+_32_35_37_38_40_42_ACTN1 NA <NA>
#> SE_2_+_32_35_37_38_ALDOA 0.09895296 two.sided
#> SE_3_+_32_35_37_38_ANXA6 0.04303647 two.sided
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.08803377 two.sided
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.09190816 two.sided
#> T-test method
#> SE_1_+_32_35_37_38_ACTN1 <NA>
#> MXE_1_+_32_35_37_38_40_42_ACTN1 <NA>
#> SE_2_+_32_35_37_38_ALDOA Welch Two Sample t-test
#> SE_3_+_32_35_37_38_ANXA6 Welch Two Sample t-test
#> MXE_2_+_32_35_37_38_40_42_ALDOA Welch Two Sample t-test
#> MXE_3_+_32_35_37_38_40_42_ANXA6 Welch Two Sample t-test
#> T-test data name
#> SE_1_+_32_35_37_38_ACTN1 <NA>
#> MXE_1_+_32_35_37_38_40_42_ACTN1 <NA>
#> SE_2_+_32_35_37_38_ALDOA vector[typeOne] and vector[!typeOne]
#> SE_3_+_32_35_37_38_ANXA6 vector[typeOne] and vector[!typeOne]
#> MXE_2_+_32_35_37_38_40_42_ALDOA vector[typeOne] and vector[!typeOne]
#> MXE_3_+_32_35_37_38_40_42_ANXA6 vector[typeOne] and vector[!typeOne]
#> ∆ Variance ∆ Median
#> SE_1_+_32_35_37_38_ACTN1 0.000000000 0.00000000
#> MXE_1_+_32_35_37_38_40_42_ACTN1 0.000000000 0.00000000
#> SE_2_+_32_35_37_38_ALDOA 0.023951168 0.13648616
#> SE_3_+_32_35_37_38_ANXA6 0.004924635 -0.01632855
#> MXE_2_+_32_35_37_38_40_42_ALDOA 0.016121555 0.15816327
#> MXE_3_+_32_35_37_38_40_42_ANXA6 0.019825834 -0.12487512