sequenza

Sequenza workflow, Given a pair of cellularity and ploidy parameters, the function returns the most likely allele-specific copy numbers with the corresponding log-posterior probability of the fit, for given values of B-allele frequency and depth ratio. Sequenza workflow, Given a pair of cellularity and ploidy parameters, the function returns the most likely allele-specific copy numbers with the corresponding log-posterior probability of the fit, for given values of B-allele frequency and depth ratio.

Overview

Overview

Dependencies

• sequenza 2.1.2m
• sequenza-scripts 2.1.5m
• sequenza-res 2.1.2

Usage

Cromwell

java -jar cromwell.jar run sequenza.wdl --inputs inputs.json

Inputs

Required workflow parameters:

Parameter	Value	Description
snpFile	File	File (data file with CNV calls from Varscan).
cnvFile	File	File (data file with SNV calls from Varscan).
reference	String	Version of genome reference

Optional workflow parameters:

Parameter	Value	Default	Description
gammaRange	Array[String]	["50", "100", "200", "300", "400", "500", "600", "700", "800", "900", "1000", "1250", "1500", "2000"]	List of gamma parameters for tuning Sequenza seqmentation step, used by copynumber package.
outputFileNamePrefix	String	""	Output prefix to prefix output file names with.

Optional task parameters:

Parameter	Value	Default	Description
preprocessInputs.rScript	String	"$RSTATS_ROOT/bin/Rscript"	path to Rscript
preprocessInputs.preprocessScript	String	"$SEQUENZA_SCRIPTS_ROOT/bin/SequenzaPreProcess_v2.2.R"	Path to the preprocessing .R script
preprocessInputs.modules	String	"sequenza/2.1.2m sequenza-scripts/2.1.5m"	modules needed to run preprocessing step
preprocessInputs.timeout	Int	20	timeout for this step in Hr, default is 20
preprocessInputs.jobMemory	Int	38	Memory allocated for this job
runSequenza.rScript	String	"$RSTATS_ROOT/bin/Rscript"	Path to Rscript
runSequenza.sequenzaScript	String	"$SEQUENZA_SCRIPTS_ROOT/bin/SequenzaProcess_v2.2.R"	Sequenza wrapper script, instructions for running the pipeline
runSequenza.modules	String	"sequenza/2.1.2m sequenza-scripts/2.1.5m sequenza-res/2.1.2"	Names and versions of modules
runSequenza.female	String?	None	logical, TRUE or FALSE. default is TRUE
runSequenza.cancerType	String?	None	acronym for cancer type (from ploidy table)
runSequenza.minReadsNormal	Float?	None	threshold of minimum number of observation of depth ratio in a segment
runSequenza.minReadsBaf	Int?	None	threshold of minimum number of observation of B-allele frequency in a segment
runSequenza.windowSize	Int	100000	parameter to define window size for segmentation
runSequenza.timeout	Int	20	Timeout in hours, needed to override imposed limits
runSequenza.jobMemory	Int	24	Memory allocated for this job
formatJson.jobMemory	Int	8	Memory allocated for this job
formatJson.width	Int	1200	width of the summary plot, default is 1200
formatJson.height	Int	400	height of the summary plot, default is 400
formatJson.modules	String	"sequenza-scripts/2.1.5m rmarkdown/0.1m"	Names and versions of modules
formatJson.summaryPlotScript	String	"$SEQUENZA_SCRIPTS_ROOT/bin/plot_gamma_solutions.R"	service script for plotting data from gamma solutions file, summary plot
formatJson.sequenzaRmd	String	"$SEQUENZA_SCRIPTS_ROOT/bin/SequenzaSummary.Rmd"	Path to rmarkdown file for producing a .pdf report
formatJson.rScript	String	"$RSTATS_ROOT/bin/Rscript"	Path to Rscript

Outputs

Output	Type	Description	Labels
resultZip	File	All results from sequenza runs using gamma sweep.	vidarr_label: resultZip
resultJson	File?	Combined json file with ploidy and contamination data.	vidarr_label: resultJson
gammaSummaryPlot	File	png for summary plot showing the effect of different gamma values	vidarr_label: gammaSummaryPlot
gammaMarkdownPdf	File	rmarkdown pdf with all gamma-specific panels along with gamma effect summary plot	vidarr_label: gammaMarkdownPdf

Commands

This section lists command(s) run by sequenza workflow

• Running sequenza

Sequenza produces the most likely allele-specific copy numbers for given values of B-allele frequency and depth ratio

Preprocessing:

   Rscript PREPROCESS_SCRIPT -s VARSCAN_SNP_FILE -c VARSCAN_CNV_FILE -y TRUE -p PREFIX
 

Prepearing data file using Varscan results:

  set -euo pipefail
  Rscript SEQUENZA_SCRIPT -s SEQZ_FILE -r REFERENCE -z GENOME_SIZE 
             -w WINDOW_SIZE 
             -g GAMMA 
             -p PREFIX 
             -l PLOIDY_FILE (Optional) 
             -f FEMALE_FLAG (Optional) 
             -t CANCER_TYPE (Optional) 
             -n MIN_READS_NORMAL (Optional) 
             -a MIN_READS_BAF (OPtional)
 
  zip -qr PREFIX_results.zip sol* PREFIX*
 

Running analysis:

  ...
  
  In this section Sequenza runs for a range of gamma values (fragment shown):
 
  cellularity = []
  ploidy = []
  no_segments = []
 
  for g in gammas:
    print(g)
    solutions = pd.read_table(os.path.join("gammas", g, "~{prefix}" + '_alternative_solutions.txt'))
    row = solutions.loc[solutions['SLPP'].idxmax()]
    cellularity.append(float(row['cellularity']))
    ploidy.append(float(row['ploidy']))
    path_seg = os.path.join("gammas", g, "~{prefix}" + '_Total_CN.seg')
    no_segments.append(len(open(path_seg).readlines()) - 1)
  
  gamma_solutions = pd.DataFrame({"gamma": gammas,
                                  "cellularity": cellularity,
                                  "ploidy": ploidy,
                                  "no_segments": no_segments})
  gamma_solutions.to_csv('gamma_solutions.csv', index=False)
 
  ...
 

Support

For support, please file an issue on the Github project or send an email to [email protected] .

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