facets-nf
Docker for IARCBioinfo/facets-nf pipeline
2.7K

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You can avoid installing all the external software by only installing Docker. See the IARC-nf repository for more information.
| Type | Description |
|---|---|
| --tumor_bam_folder | Folder containing tumor BAM files |
| --normal_bam_folder | Folder containing normal BAM files |
| OR | |
| --bam_folder | Folder containing all BAM files (without "/" at the end) |
| --tn_file | File containing the list of names of BAM files to be processed - by pairs T/N (tab-delimited as follow: T.bam, N.bam) |
| Name | Example value | Description |
|---|---|---|
| --ref | hg19/hg38 | Version of genome: hg19 or hg38 |
| --dbsnp_vcf_ref | ref/dbsnp_vcf_ref | Path to dbsnp vcf reference |
Dbsnp vcf reference can be downloaded for:
hg19: wget ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606_b150_GRCh37p13/VCF/00-common_all.vcf.gz
hg38: wget ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606_b150_GRCh38p7/VCF/00-common_all.vcf.gz
| Name | Default value | Description |
|---|---|---|
| --mem | 4 GB | memory allocated to each nextflow process |
| --snppileup_bin | snp-pileup | Path to snppileup software (default: snp-pileup) |
| --analysis_type | genome/exome | Type of analysis: whole genome (by default) or whole exome - sets next five parameters values |
| --snp_nbhd | 1000 or 250 | 1st value for genome, 2nd value for exome analysis |
| --cval_preproc | 35 por 25 | 1st value for genome, 2nd value for exome analysis |
| --cval_proc1 | 300 or 150 | 1st value for genome, 2nd value for exome analysis |
| --cval_proc2 | 150 or 75 | 1st value for genome, 2nd value for exome analysis |
| --min_read_count | 20 or 35 | 1st value for genome, 2nd value for exome analysis |
| --suffix_tumor | "_T" | specific suffix for tumor bam file name |
| --suffix_normal | "_N" | specific suffix for normal bam file name |
| --min-map-quality | 15 | |
| --min-base-quality | 20 | |
| --pseudo-snps | 100 | |
| --facets_stats_out | facets_stats_summary.txt | Name of stats summary file |
| --out_folder | facets_out | Folder name for output files (by default current folder) |
Flags are special parameters without value.
| Name | Description |
|---|---|
| --help | Display help |
| --output_pdf | Program outputs a (large) pdf instead of png |
nextflow run iarcbioinfo/facets-nf --tumor_bam_folder path/to/T_BAMS --normal_bam_folder path/to/N_BAMS --analysis_type genome --ref hg38 --dbsnp_vcf_ref path/to/dbSNP_vcf_ref.vcf.gz
| Type | Description |
|---|---|
| All_stats.txt | Stats for all samples pooled |
| Sample_CNV.txt | A few stats for the sample |
| Sample_CNV_spider.txt | spider plot for parameter estimates |
| Sample_CNV.png or Sample_CNV.pdf | output plot of CNV |
| Sample.RData | R object with 5 objects (xx,oo_large,fit_large,oo_fine,fit_fine) |
In Sample.RData:
xx corresponds to the pre-processed data using the segmentation critical value cval_preproc (output of function preProcSample)
oo_large corresponds to the processing of xx using the segmentation critical value cval_proc1 (output of function procSample(xx,cval = cval_proc1,...) )
fit_large: cluster specific copy number and cellular fraction (output of emcncf(oo_large))
oo_fine corresponds to the processing of xx using the segmentation critical value cval_proc2 (output of procSample(xx, cval = cval_proc2, ...))
fit_fine: cluster specific copy number and cellular fraction ( output of emcncf(oo_fine))
In case of low coverage you may get the following error during facets process:
Loading required package: pctGCdata
Error in fit.cpt.tree(genomdat, cval = cval, hscl = hscl, delta = delta) :
NA/NaN/Inf in foreign function call (arg 9)
Calls: preProcSample -> segsnps -> fit.cpt.tree
=> We advise then to decrease the parameter: min_read_count
| Name | Description | |
|---|---|---|
| Matthieu Foll* | [email protected] | Developer to contact for support (link to specific gitter chatroom) |
| Catherine Voegele | [email protected] | Developer |
| Nicolas Alcala | [email protected] | Developer |
Content type
Image
Digest
Size
604.2 MB
Last updated
over 5 years ago
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