1. Preliminary analysis - SC

The pre-processing workflows extract clean s-reads using tools below which can then be provided to the alignment applications and other downstream workflows similar to those used to analyze Isoseq data. High level pre-processing is adopted from Pacbio’s CLI workflow

• skera for deconcatenating the MAS arrays into individual cDNA molecules and generate segmented reads (s-reads),

• lima for removal of primers and identification of barcodes and orienting sequences in 5’ → 3’ orientation.

• isoseq tag to clip tags (cell barcode, UMI, Gs). Supports design presets and custom experimental designs.

• isoseq refine for trimming poly(A) tails and extracting Full length non-concatemer reads (FLNC) from s-reads.

• isoseq correct for correcting errors in cell barcodes, the total number of usable reads increased (typically ~5%)

1.1. pbskera

The pbskera workflow, as detailed below, processes raw HiFi reads generated with Sequel2e and Revio Long Read sequencers. The HiFi reads are a current default, and can be plugged in directly into the workflow to get segmented s-reads.

Workflow configuration for runnning these over cloud platforms supporting Cromwell like Terra can be found here:-

Dockstore : skera_w_QCplots.wdl

Github: Kinnex Preliminary Processing

Test Data can be found here (public, requester-pays) : gs://fc-secure-6b69ce23-e507-4375-929c-75ab7213f277/kinnex_sc/m84014_240128_083549_s3_sub0005.hifi_reads.bcM0003.bam

The direct command executed here is:

    skera split –j 16 reads.hifi.bam mas16_adapters.fasta reads.skera.bam

Input arguments for pbskera_main

Table 7 skera

Option name	example value	description
input_bam	this.input_bam	Replace “input_bam” with the column that contains the path to the input file in the sample table.
arraysize	8	Size of the MAS array, could be 8, 16 or 12 depending upon the library type
mas_adapters_fasta	“gs://mdl-preprocess-refs/MAS_adapters/mas8_primers.fasta”	MAS adapters FASTA file for de-concatenation. Ref files can be found at gs://mdl-preprocess-refs/MAS_adapters/
sample_id	this.movie_name	Replace “sample_id” with the column that contains the name of the samples in the sample table. Recommended id is the movie name
gcs_output_dir	“gs://output_dir/”	Output directory to organize intermediates and QC plots
num_threads	8	Number of threads (set atleast equal to the number of cpu)
cpu	8	Number of cpus

Example of QC plots generated :

Fig. 8 Read Length Histogram

Fig. 9 Ligation Heatmap

Fig. 10 Concatenation Histogram

For a 16-mer we expect the plots to be similar to as above, with maximum number of reads assigned to a complete 16-mer configuration. In addition, to the readlength plot, the concatenation histogram should also indicate high percentages (>90%) to be assigned to a concatenation factor of 16. The ligation heatmap distributes the number of reads by adapter pairs found in the array. They should cleanly align along the diagonal for a well-performing array.

1.2 pblima + isoseq tag + isoseq refine + isoseq correct

This workflow uses 2 tools to extract clean s-reads from the skera.bam received above namely lima and isoseq.

Workflow configuration for runnning these over cloud platforms supporting Cromwell like Terra can be found here:-

Dockstore : `sc_kinnex_lima_plus_isoseq.wdl <>`_

Github : Kinnex Single Cell Preliminary Processing

Test Data: gs://fc-secure-6b69ce23-e507-4375-929c-75ab7213f277/kinnex_sc/m84014_240128_083549_s3_sub0005.bcM0003.skera.bam (public, requester-pays)

Example of input arguments for the workflow for 10x 3p kit

{
 "pb_sc_lima_isoseq.sample_id": "${this.movie_name}",
 "pb_sc_lima_isoseq.barcodes_list": "gs://mdl-preprocess-refs/10x_barcodes/3M-february-2018-REVERSE-COMPLEMENTED.txt.gz",
 "pb_sc_lima_isoseq.primer_fasta": "gs://mdl-preprocess-refs/REF-10x_primers/10x_3kit_primers.fasta",
 "pb_sc_lima_isoseq.gcs_output_dir": "${this.out_path}",
 "pb_sc_lima_isoseq.skera_bam": "${this.skera_bam}",
 "pb_sc_lima_isoseq.read_design": "T-12U-16B"
 }