lofreq/lofreq_call

variant calling
low frequancy variant calling
lofreq
lofreq/call

Description

Call variants from a BAM file.

LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or base/indel alignment uncertainty), which are usually ignored by other methods or only used for filtering.

LoFreq* can run on almost any type of aligned sequencing data (e.g. Illumina, IonTorrent or Pacbio) since no machine- or sequencing-technology dependent thresholds are used. It automatically adapts to changes in coverage and sequencing quality and can therefore be applied to a variety of data-sets e.g. viral/quasispecies, bacterial, metagenomics or somatic data.

LoFreq* is very sensitive; most notably, it is able to predict variants below the average base-call quality (i.e. sequencing error rate). Each variant call is assigned a p-value which allows for rigorous false positive control. Even though it uses no approximations or heuristics, it is very efficient due to several runtime optimizations and also provides a (pseudo-)parallel implementation. LoFreq* is generic and fast enough to be applied to high-coverage data and large genomes. On a single processor it takes a minute to analyze Dengue genome sequencing data with nearly 4000X coverage, roughly one hour to call SNVs on a 600X coverage E.coli genome and also roughly an hour to run on a 100X coverage human exome dataset.

Type

bash_script

License

MIT

Keywords

variant calling
low frequancy variant calling
lofreq
lofreq/call

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
out: "$id.$key.out.vcf"  
id: "run"  
publish_dir: "output/"  
EOM

nextflow run https://packages.viash-hub.com/vsh/biobox.git \  
  -revision v0.1.0 \  
  -main-script target/nextflow/lofreq/lofreq_call/main.nf \  
  -params-file params.yaml  

Inputs

Name
Type & Properties
--input
file
required
--input_bai
file
required
--ref
-f
file
required

Outputs

Name
Type & Properties
--out
-o
file
required
output

Arguments

Name
Type & Properties
--region
-r
string
--bed
-l
file
--min_bq
-q
integer
--min_alt_bq
-Q
integer
--def_alt_bq
-R
integer
--min_jq
-j
integer
--min_alt_jq
-J
integer
--def_alt_jq
-K
integer
--no_baq
-B
boolean_true
--no_idaq
-A
boolean_true
--del_baq
-D
boolean_true
--no_ext_baq
-e
boolean_true
--min_mq
-m
integer
--max_mq
-M
integer
--no_mq
-N
boolean_true
--call_indels
boolean_true
--only_indels
boolean_true
--src_qual
-s
boolean_true
--ign_vcf
-S
file
--def_nm_q
-T
integer
--sig
-a
double
--bonf
-b
string
--min_cov
-C
integer
--max_depth
-d
integer
--illumina_13
boolean_true
--use_orphan
boolean_true
--plp_summary_only
boolean_true
--no_default_filter
boolean_true
--force_overwrite
boolean_true
--verbose
boolean_true
--debug
boolean_true

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Viash Hub is a platform developed by Data Intuitive, a Belgian-based bioinformatics company specializing in data workflow development and deployment.