NIPT_Diagnostics_v3.0_QC_Report.Rmd

QC Report `r samplename`
=======================================================
`r format(Sys.Date(), format=("%d %B %Y"))`

##Prediction Statistics Regression Models
```{r echo=FALSE, results= 'asis'}
PS13 <- PredictionStatistics13

datafrPS13 <- data.frame(PS13)

#Transform to table
tab <- xtable(datafrPS13, align = "ccccc")
print(tab, type="html")
```
<br>
```{r echo=FALSE, results= 'asis'}
PS18 <- PredictionStatistics18

datafrPS18 <- data.frame(PS18)

#Transform to table
tab <- xtable(datafrPS18, align = "ccccc")
print(tab, type="html")
```
<br>
```{r echo=FALSE, results= 'asis'}
PS21 <- PredictionStatistics21

datafrPS21 <- data.frame(PS21)

#Transform to table
tab <- xtable(datafrPS21, align = "ccccc")
print(tab, type="html")
```

<br>

###Standard Z-score calculations using GC corrected data
```{r echo=FALSE, results='asis'}
library(xtable)

#Build list from variables
Variation_coefficient <- c(format(CV13, digits = 2), format(CV18, digits = 2), format(CV21, digits = 2) )
Normal_Distribution <- c(format(Normal13), format(Normal18), format(Normal21) ) 
Z_score <- c(format(Z_score13, digits = 3), format(Z_score18, digits = 3), format(Z_score21, digits = 3) )

datafrZscore <- data.frame(Variation_coefficient,Normal_Distribution,Z_score, row.names = c("Chr 13","Chr 18","Chr 21"))

#Transform to table
tab <- xtable(datafrZscore, align = "cccc")
print(tab, type="html")

```


<br>
All other chromosomes have a normal Z-score: `r toString(All_chromosomes_norm_Zscore[[1]])`
<br>

###Average Matchscore sample to control group
The average Matchscore of the sample compared with the current control group is `r format(AvMatchScore[[1]], digit=4)`
<br><br>

###Matchscore list
```{r echo=FALSE, results = 'asis'}
MatchScore <- format(MatchScorelist, digits = 3)
datafrMSc <- data.frame(MatchScore)

#Transform to table
tab <- xtable(datafrMSc, align = "cc")
print(tab, type="html")


```