Freemuxlet

Freemuxlet is a software tool to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing.

Info

ID: freemuxlet
Namespace: genetic_demux

If external genotyping data is not available, the genotyping-free version demuxlet, freemuxlet, would be recommended

Example commands

You can run the pipeline using nextflow run.

View help

You can use --help as a parameter to get an overview of the possible parameters.

nextflow run openpipelines-bio/openpipeline \
  -r 1.0.2 -latest \
  -main-script target/nextflow/genetic_demux/freemuxlet/main.nf \
  --help

Run command

Example of params.yaml 
# Input
# plp: "foo"
# init_cluster: "path/to/file"
nsample: 2
aux_files: false
verbose: 100
doublet_prior: 0.5
geno_error: 0.1
bf_thres: 5.41
frac_init_clust: 1
iter_init: 10
keep_init_missing: false
randomize_singlet_score: false
seed: 0
cap_bq: 20
min_bq: 13
# group_list: "foo"
min_total: 0
min_umi: 0
min_snp: 0

# Output
# output: "$id.$key.output.output"
# out: "freemuxlet"

# Nextflow input-output arguments
publish_dir: # please fill in - example: "output/"
# param_list: "my_params.yaml"
nextflow run openpipelines-bio/openpipeline \
  -r 1.0.2 -latest \
  -profile docker \
  -main-script target/nextflow/genetic_demux/freemuxlet/main.nf \
  -params-file params.yaml
Note

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

Argument groups

Input

Name Description Attributes
--plp Prefix of input files generated by dsc-pileup string
--init_cluster Input file containing the initial cluster information. file
--nsample Number of samples multiplexed together integer, default: 2
--aux_files Turn on writing auxilary output files boolean_true
--verbose Turn on verbose mode with specific verbosity threshold. 0: fully verbose, 100 : no verbose messages. integer, default: 100
--doublet_prior Prior of doublet. double, default: 0.5
--geno_error Genotype error parameter per cluster. double, default: 0.1
--bf_thres Bayes Factor Threshold used in the initial clustering. double, default: 5.41
--frac_init_clust Fraction of droplets to be clustered in the very first round of initial clustering procedure. double, default: 1
--iter_init Iteration for initial cluster assignment (set to zero to skip the iterations). integer, default: 10
--keep_init_missing Keep missing cluster assignment as missing in the initial iteration. boolean_true
--randomize_singlet_score Randomize the singlet scores to test its effect. boolean_true
--seed Seed for random number (use clocks if not set). integer, default: 0
--cap_bq Maximum base quality (higher BQ will be capped). integer, default: 20
--min_bq Minimum base quality to consider (lower BQ will be skipped). integer, default: 13
--group_list List of tag readgroup/cell barcode to consider in this run. All other barcodes will be ignored. This is useful for parallelized run. string
--min_total Minimum number of total reads for a droplet/cell to be considered. integer, default: 0
--min_umi Minimum number of UMIs for a droplet/cell to be considered. integer, default: 0
--min_snp Minimum number of SNPs with coverage for a droplet/cell to be considered. integer, default: 0

Output

Name Description Attributes
--output Output directory file, example: "freemux"
--out freemuxlet Output file prefix string, example: "freemuxlet"

Authors

  • Xichen Wu (author)