Data overview

Overview

We collected two types of data for each single cell sample: single-cell RNA-seq using C1 plates and FUCCI image intensity data.

• Raw RNA-seq data: data/eset-raw.rds

• Filtered RNA-seq data: data/eset-filtered.rds

• FUCCI intensity data: data/intensity.rds

• FUCCI intensity data adjusted for batch effect: output/images-normalize-anova.Rmd/pdata.adj.rds

• Final data combining filtered intensity and RNA-seq, including 11093 genes and 888 samples: data/eset-final.rds

Code used to generate data from data/eset-raw.rds to data/eset-final.rds is stored in code/output-raw-2-final.R.

FUCCI intensity data

• Combined intensity data are stored in data/intensity.rds. These include samples that were identified to have a single nuclei .

• Data generated by [combine-intensity-data.R][data/combine-intensity-data.R]. Combining image analysis output stored in /project2/gilad/fucci-seq/intensities_stats/ into one data.frame and computes summary statistics, including background-corrected RFP and GFP intensity measures.

Sequencing data

• Raw data from each C1 plate are stored separatley in data/eset/ by experiment (batch) ID.

• Raw data combining C1 plate are stored in data/eset-raw.rds.

• Filtered raw data excluding low-quality sequencing samples and genes that are lowly expressed or overly expressed are stored in data/eset-filtered.rds..

Access expressionSets

We store feature-level (gene) read count and molecule count in expressionSet (data/eset) objects, which also contain sample metadata (e.g., assigned indivdual ID, cDNA concentraion) and quality filtering criteria (e.g., number of reads mapped to FUCCI transgenes, ERCC conversion rate). Data from different C1 plates are stored in separate eset objects:

To combine eset objects from the different C1 plates:

eset <- Reduce(combine, Map(readRDS, Sys.glob("data/eset/*.rds")))

To access data stored in expressionSet:

• exprs(eset): access count data, 20,421 features by 1,536 single cell samples.

• pData(eset): access sample metadata. Returns data.frame of 1,536 samples by 43 labels. Use varMetadata(phenoData(eset)) to view label descriptions.

• fData(eset): access feature metadata. Returns data.frame of 20,421 features by 6 labels. Use varMetadata(featureData(eset)) to view label descriptions.

• varMetadata(phenoData(eset)): view the sample metadata labels.

• varMetadata(featureData(eset)): view the feature (gene) metadata labels.

Session information

R version 3.4.1 (2017-06-30)
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: Scientific Linux 7.2 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] compiler_3.4.1  backports_1.1.2 magrittr_1.5    rprojroot_1.3-2
 [5] tools_3.4.1     htmltools_0.3.6 yaml_2.1.18     Rcpp_0.12.16   
 [9] stringi_1.1.7   rmarkdown_1.9   knitr_1.20      git2r_0.21.0   
[13] stringr_1.3.0   digest_0.6.15   evaluate_0.10.1