Data Summary

This is a summary of the given data matrix for the first 12 genes.

Table continues below
V1 V2 V3 V4 V5 V6
Min. :-12604 Min. :-44084 Min. :-44292 Min. :-41722 Min. :-30883 Min. :-39013
1st Qu.: 2989 1st Qu.: -991 1st Qu.: -7291 1st Qu.: 2211 1st Qu.: 7771 1st Qu.:-13232
Median : 15994 Median : 6606 Median : 14936 Median : 7893 Median : 14603 Median : 9192
Mean : 37683 Mean : 49338 Mean : 57977 Mean : 29429 Mean : 33795 Mean : 42882
3rd Qu.: 44817 3rd Qu.: 68296 3rd Qu.: 79724 3rd Qu.: 45117 3rd Qu.: 47537 3rd Qu.: 78539
Max. :307823 Max. :440159 Max. :556646 Max. :360476 Max. :235209 Max. :506643
V7 V8 V9 V10 V11 V12
Min. : -5795 Min. :-10572 Min. : -4450 Min. :-49930 Min. :-11622 Min. :-49517
1st Qu.: 4536 1st Qu.: 2962 1st Qu.: 4015 1st Qu.: -3530 1st Qu.: -5586 1st Qu.: 3550
Median : 16088 Median : 14421 Median : 12456 Median : 13522 Median : 1783 Median : 29970
Mean : 43854 Mean : 40153 Mean : 39100 Mean : 57801 Mean : 38532 Mean : 61492
3rd Qu.: 59052 3rd Qu.: 61603 3rd Qu.: 54528 3rd Qu.: 78275 3rd Qu.: 20032 3rd Qu.: 94972
Max. :325854 Max. :207735 Max. :236775 Max. :580687 Max. :533742 Max. :311919

Heatmap

This is a heatmap of the given data matrix showing the batch effects and variations with different conditions.

## Warning in t(log2(t(qcounts + 0.5)/(lib.size + 1) * 1e+06)): NaNs produced

PCA: Principal Component Analysis

This is a plot of the top two principal components and showing the variation with respect to batch effects and different conditions.

PCA Proportion Variation and correlation

PCA Proportion Variation and correlation Table

Percentage Variation Cumulative Percentage Variation Condition Correlation Batch Correlation
17.62 17.62 1.18 0.1
8.32 25.94 0.04 0.75
7.35 33.29 0.96 0
6.79 40.08 0.96 0.06
5.86 45.94 0.06 0.05
5.76 51.7 1.07 0.13
4.76 56.46 0.05 0.38
4.13 60.59 0.28 0.88
3.75 64.34 0.17 0.02
3.47 67.81 7.53 0.47
3.01 70.82 0.19 0.12
2.77 73.59 0.37 0.04
2.64 76.23 0.54 0
2.31 78.54 0.08 0.79
2.24 80.78 0.95 0.24
1.93 82.71 0.23 0.82
1.76 84.47 0.2 0.44
1.65 86.12 0.77 0.01
1.4 87.52 6.91 1.56
1.4 88.92 0.02 0.01
1.23 90.15 0.38 0.54
1.13 91.28 2.2 0.14
0.97 92.25 1.83 0.02
0.87 93.12 0.35 0.72
0.84 93.96 0.03 0
0.78 94.74 0.03 1.04
0.64 95.38 0.13 3.91
0.64 96.02 2.06 1.9
0.52 96.54 0.6 0.21
0.47 97.01 0.15 0.09
0.44 97.45 1.83 0.56
0.38 97.83 0.35 0.09
0.34 98.17 2.37 0.24
0.33 98.5 0.55 0.05
0.29 98.79 3.3 0.01
0.22 99.01 1.28 19.19
0.2 99.21 0.44 0.22
0.15 99.36 7.16 0.93
0.14 99.5 2.09 5.57
0.12 99.62 4.16 0.03
0.1 99.72 3.26 0.79
0.08 99.8 5.66 0.25
0.06 99.86 8.96 2.78
0.05 99.91 0.47 3
0.05 99.96 0.11 0.28
0.03 99.99 2.89 0.74
0.01 100 1.05 1.72
0.01 100 0.2 0.56
0.01 100 5.43 2.26
0 100 0.51 18.22

Combat Plots

This is a plot showing whether parametric or non-parameteric prior is appropriate for this data. It also shows the Kolmogorov-Smirnov test comparing the parametric and non-parameteric prior distribution.

## Found 3 batches
## Adjusting for 1 covariate(s) or covariate level(s)
## Standardizing Data across genes
## Fitting L/S model and finding priors

## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  gamma.hat[1, ]
## D = 0.1314, p-value = 0.3247
## alternative hypothesis: two-sided

Batch Effects testing

This is a summary of the statistical test for batch effects.

## 
## Call:
## lm(formula = pc[, 1] ~ fbatch + fcond)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.5145 -1.4447 -0.0521  1.0365  7.8306 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.037806   0.501615  -0.075    0.940
## fbatch2     -0.158730   0.614350  -0.258    0.797
## fbatch3      0.260921   0.614350   0.425    0.673
## fcond1       0.007485   0.501615   0.015    0.988
## 
## Residual standard error: 1.943 on 56 degrees of freedom
## Multiple R-squared:  0.008429,   Adjusted R-squared:  -0.04469 
## F-statistic: 0.1587 on 3 and 56 DF,  p-value: 0.9236
## 
## 
## Call:
## lm(formula = pc[, 2] ~ fbatch + fcond)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7701 -0.9974  0.1485  1.0928  4.1527 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)  0.21686    0.47747   0.454    0.651
## fbatch2      0.05129    0.58477   0.088    0.930
## fbatch3     -0.35070    0.58477  -0.600    0.551
## fcond1      -0.23410    0.47747  -0.490    0.626
## 
## Residual standard error: 1.849 on 56 degrees of freedom
## Multiple R-squared:  0.01409,    Adjusted R-squared:  -0.03873 
## F-statistic: 0.2668 on 3 and 56 DF,  p-value: 0.8491
## 
## 
## Call:
## lm(formula = pc[, 3] ~ fbatch + fcond)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.9757 -1.0662 -0.0300  0.7505  6.6574 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   0.3296     0.4737   0.696    0.489
## fbatch2      -0.3233     0.5801  -0.557    0.580
## fbatch3      -0.1741     0.5801  -0.300    0.765
## fcond1       -0.3276     0.4737  -0.692    0.492
## 
## Residual standard error: 1.835 on 56 degrees of freedom
## Multiple R-squared:  0.01391,    Adjusted R-squared:  -0.03892 
## F-statistic: 0.2632 on 3 and 56 DF,  p-value: 0.8516
## 
## 
## Call:
## lm(formula = pc[, 4] ~ fbatch + fcond)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.7969 -0.9759 -0.1549  0.6747  5.7618 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.056593   0.430820  -0.131    0.896
## fbatch2     -0.148710   0.527645  -0.282    0.779
## fbatch3      0.004913   0.527645   0.009    0.993
## fcond1       0.209051   0.430820   0.485    0.629
## 
## Residual standard error: 1.669 on 56 degrees of freedom
## Multiple R-squared:  0.006123,   Adjusted R-squared:  -0.04712 
## F-statistic: 0.115 on 3 and 56 DF,  p-value: 0.951
## 
## 
## Call:
## lm(formula = pc[, 5] ~ fbatch + fcond)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.1618 -1.0288  0.1618  0.9011  5.2336 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)  -0.2596     0.4177  -0.621    0.537
## fbatch2       0.2651     0.5115   0.518    0.606
## fbatch3      -0.3842     0.5115  -0.751    0.456
## fcond1        0.5985     0.4177   1.433    0.157
## 
## Residual standard error: 1.618 on 56 degrees of freedom
## Multiple R-squared:  0.06171,    Adjusted R-squared:  0.01145 
## F-statistic: 1.228 on 3 and 56 DF,  p-value: 0.3082