Smart-Seq2 quality control pipeline

Smart-seq2 quantification and quality control pipeline, developed for single-cell service at the Earlham Institue. version 1.1

Starting with the FASTQ files generated from the SmartSeq2 experiment and a sample sheet containing the appropriate metadata, transcript level counts are generated, merged and used to produce QC metrics. A QC report document is generated for each of the plates, and the whole experiment.

The pipeline does not require internet connection, but some required files have to be precomputed.

Inputs

• Config file

Outputs

• Sample count quantifications
• Expression counts matrix (transcript and gene-level)
• Quality control metrics and plots (per plate)
• QC report (per plate and for the entire experiment)

Tools used

• kallisto 0.48.0
• nextflow
• R and R packages (scater 1.28.0, rjson 0.2.21, rmarkdown, tinytex, knitr, dplyr)
• singularity 2.4.2
• pandoc, texlive, ghostscript

Preprocessing

1. convert the sample sheet to UNIX format

source dos2unix-7.4.1_CBG
dos2unix -n old_samplesheet samplesheet

2. format read names. The pipeline can take symbolic links and requires read names in the following format:

${Sample_Plate}_${demultiplexed_readname}

For example, the following FASTQ file from plate CUB35DAY0 with a filename:

R0882-S0001_A68701_CUB35DAY0A10_H3VY5DRX2_CGTACTAG-AGAGGATA_L001_R1.fastq.gz

becomes

CUB35DAY0_R0882-S0001_A68701_CUB35DAY0A10_H3VY5DRX2_CGTACTAG-AGAGGATA_L001_R1.fastq.gz

Running the pipeline

Pipeline is written in Nextflow, so a run is usually initiated in the following way: nextflow run scqc_nf.sh -c config_file &

Examples of a config file and sample sheet are in the repository.

An example:

cd /ei/cb/development/lany/CB-GENANNO-525_Charlotte_Utting_EI_CU_ENQ-5286_A_01/Analysis/scqc_reqs-1.1/4plates.run2
sbatch -p ei-cb -J scqc_GENANNO-525.all_plate -o scqc_GENANNO-525.all_plate.%j.%N.log -c 1 --mem 10G \
    --mail-type=ALL --mail-user=user.email.com \
    --wrap "source singlecellQC-1.1_CBG && cd $analysis_dir && \
    nextflow run /ei/software/cb/singlecellQC/1.1/x86_64/bin/scqc_nf.sh \
    -c GENANNO-525.scqc-1.1.all_plates.config -with-report -resume"

Config file

Parameters inside 'params' scope can be passed when starting the pipeline by adding them at the end of the pipeline start call, e.g. 'nextflow run scqc_nf.sh -c scqc.config --qcoutdir=my_qc_directory'. Alternatively, they can be edited in the config file.

Parameters related to the output, organism species and this pipeline.

• quantificationsdir - Directory to contain qunatifications produced for each of the samples and the counts matrices
• qcoutdir' - Directory to contain the final QC report and other QC-related files
• samplesheet - .csv file containing information about sample names, wells, control status and other sample metadata.
• reads - Location of sample FASTQ files.
• species - E.g., 'Hsapiens', 'Mmusculus'.
• plate_ids - List of plate identificators (typically 4 strings), as they appear in the names of raw data samples. This is how the pipeline merges samples into plate-level matrices which are then used for plate-level QC.
• mtnamefile - In case of non-human species, .rds file for mitochondrial gene. Leave empty ('') if human. This is a vector in R, containing the list of Ensembl transcript IDs, saved as .rds (using saveRDS())
• pattern - The format of the FASTQ endings showing how they should be grouped, as a glob pattern
• trans2gen_tsv - Transcript id to gene id mapping tsv file

General HPC parameters in scope executor:

• executor - Type of HPC scheduler.

• queue - Queue used for submitting jobs.

• memory - Memory assigned to a job.

• queueSize - Maximum number of jobs the pipeline will submit at once.

Process specific parameters can be set in scope process.

For more information on configuration file options, check out nextflow documentation.

Sample sheet

Sample sheet will be unique for every run.

It is a .csv file that has to have the following columns. Additional columns are not a problem, but are not used. Make sure there is no white space in any entries.

• Sample_ID, Sample_Name - These two columns are also in the Illumina sample sheet.
• Sample_Plate - A string corresponding to one of the plates used in the experiment
• Sample_Well - Row/column location of the sample on the plate. Something like A01, A02, etc. These are needed for plate position plots.
• row - Row location of the sample on the plate. Normally ranges between A to H.
• column - Column location of the sample on the plate. Normal range is between 1 and 12.
• control - TRUE if the well contains a control, FALSE otherwise.
• number_of_cells - Number of cells in a well, e.g., 0, 1, 2, 20, 50. Wells contains more or less than 1 cells will be labeled as "control".
• meta_1: meta data field 1, catagorical value.
• meta_2: meta data field 2, catagorical value

Required precomputed resources

• kallisto index
• list of mitochondrial genes
• transcript id to gene id mapping tsv file
• singularity images