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Started on 2017-09-05 12:54:20

FastQC_Result

Read Counts

The read counts in each sample.

Per Base Read Quality

The black and white heatmaps show the average reads quality
over all samples per base. The color scale corresponds to the percentage of reads at each reads quality.

The blue and read heatmaps show the difference between each sample’s reads quality and the average reads quality per base. The red represents a higher percentage of reads over the average, while the blue represents a lower percentage of reads over the average.

Correlation

Correlation between Library concentration measurements and ReadCounts. It’s only shown when “LibConc_qPCR” or “LibConc_100_800bp” columns exit in dataset.

Heatmaps of reads/concentration per cell on the plate

Sequenced reads or concentration per cell, on the plate layout. The current supported plate layout format is “PlateNumber_[A-Z][Integer]”, e.g. “1_A2”. Otherwise, the platelayout is not shown.

The heatmap values are in \(log10\) scale. The colorScale ranges from half of median value to twice of median value.

Input Dataset

SessionInfo

## R version 3.4.0 (2017-04-21)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 8 (jessie)
## 
## Matrix products: default
## BLAS: /usr/lib/atlas-base/atlas/libblas.so.3.0
## LAPACK: /usr/lib/atlas-base/atlas/liblapack.so.3.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=de_DE.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=de_DE.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
##  [1] grid      stats4    parallel  stats     graphics  grDevices utils    
##  [8] datasets  methods   base     
## 
## other attached packages:
##  [1] htmltools_0.3.6      DT_0.2               gridExtra_2.2.1     
##  [4] reshape2_1.4.2       plotly_4.7.0         ggplot2_2.2.1       
##  [7] rmarkdown_1.5        ezRun_1.0.15         GenomicRanges_1.28.3
## [10] GenomeInfoDb_1.12.0  Biostrings_2.44.0    XVector_0.16.0      
## [13] IRanges_2.10.1       S4Vectors_0.14.1     BiocGenerics_0.22.0 
## [16] data.table_1.10.4   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_0.12.11            highr_0.6              
##  [3] compiler_3.4.0          plyr_1.8.4             
##  [5] bitops_1.0-6            tools_3.4.0            
##  [7] zlibbioc_1.22.0         digest_0.6.12          
##  [9] viridisLite_0.2.0       jsonlite_1.4           
## [11] evaluate_0.10           tibble_1.3.3           
## [13] gtable_0.2.0            rlang_0.1.1            
## [15] shiny_1.0.3             crosstalk_1.0.0        
## [17] yaml_2.1.14             GenomeInfoDbData_0.99.0
## [19] httr_1.2.1              stringr_1.2.0          
## [21] dplyr_0.7.0             knitr_1.16             
## [23] htmlwidgets_0.8         rprojroot_1.2          
## [25] glue_1.1.0              R6_2.2.1               
## [27] tidyr_0.6.3             purrr_0.2.2.2          
## [29] magrittr_1.5            backports_1.1.0        
## [31] scales_0.4.1            assertthat_0.2.0       
## [33] xtable_1.8-2            mime_0.5               
## [35] colorspace_1.3-2        httpuv_1.3.3           
## [37] labeling_0.3            stringi_1.1.5          
## [39] RCurl_1.95-4.8          lazyeval_0.2.0         
## [41] munsell_0.4.3