Sniffles version 2.0.2

LICENSE

@@ -1,6 +1,6 @@
-The MIT License (MIT)
+MIT License
 
-Copyright (c) 2015 Fritz Sedlazeck
+Copyright (c) 2021 Moritz Smolka
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
@@ -19,4 +19,3 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
-

README.md

@@ -1,63 +1,61 @@
-# Sniffles
-Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs (10bp+) using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter), Minimap2 (sam file with Cigar & MD string) or NGMLR. If you experience problems or have suggestions please contact: [email protected]
+# Sniffles2
+A fast structural variant caller for long-read sequencing, Sniffles2 accurately detect SVs on germline, somatic and population-level for PacBio and Oxford Nanopore read data.
 
+## Quick Start: Germline SV calling using Sniffles2
+To call SVs from long read alignments (PacBio / ONT), you can use:
 
-Please see our github wiki for more information (https://github.com/fritzsedlazeck/Sniffles/wiki)
+`sniffles -i mapped_input.bam -v output.vcf`
 
+(see sniffles --help or below for full usage information)
 
-# How to build Sniffles
-<pre>wget https://github.com/fritzsedlazeck/Sniffles/archive/master.tar.gz -O Sniffles.tar.gz
-tar xzvf Sniffles.tar.gz
-cd Sniffles-master/
-mkdir -p build/
-cd build/
-cmake ..
-make
+## Installation
+You can install Sniffles2 using pip or conda using:
 
-cd ../bin/sniffles*
-./sniffles</pre>
+`pip install sniffles`
 
-Note Mac users often have to provide parameters to the cmake command:
-<pre>cmake -D CMAKE_C_COMPILER=/opt/local/bin/gcc-mp-4.7 -D CMAKE_CXX_COMPILER=/opt/local/bin/g++-mp-4.7 .. 
-</pre>
+or
 
+`conda install sniffles`
 
-**************************************
-## NGMLR
-Sniffles performs best with the mappings of NGMLR our novel long read mapping method. 
-Please see:
-https://github.com/philres/ngmlr
+## Requirements
+* Python >= 3.7
+* pysam
 
-****************************************
-## Citation:
-Please see and cite our paper:
-https://www.nature.com/articles/s41592-018-0001-7
-
-**************************************
-## Poster & Talks:
+#### Tested on:
+* python==3.9.5
+* pysam==0.16.0.1
 
-[Accurate and fast detection of complex and nested structural variations using long read technologies](http://schatzlab.cshl.edu/presentations/2016/2016.10.28.BIODATA.PacBioSV.pdf)
-Biological Data Science, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 26 - 29.10.2016
+## Use-Cases / Modes
 
-[NGMLR: Highly accurate read mapping of third generation sequencing reads for improved structural variation analysis](http://www.cibiv.at/~philipp_/files/gi2016_poster_phr.pdf) 
-Genome Informatics 2016, Wellcome Genome Campus Conference Centre, Hinxton, Cambridge, UK, 19.09.-2.09.2016
+### A. General (all Modes)
+* To output deletion (DEL SV) sequences, the reference genome (.fasta) must be specified using e.g. `--reference reference.fasta`.
+* Sniffles2 supports optionally specifying tandem repeat region annotations (.bed), which can improve calling in these regions `--tandem-repeats annotations.bed`. Sniffles2 tandem repeat annotations are compatible with those from pbsv, which for human references can be downloaded at their [GitHub repository](https://github.com/PacificBiosciences/pbsv/blob/master/annotations/).
+* Sniffles2 is fully parallelized and uses 4 threads by default. This value can be adapted using e.g. `--threads 4` as option. Memory requirements will increase with the number of threads used.
+* To output read names in SNF and VCF files, the `--output-rnmaes` option is required.
 
-**************************************
-## Datasets used in the mansucript:
-We provide the NGMLR aligned reads and the Sniffles calls for the data sets used:  
+### B. Multi-Sample SV Calling (Trios, Populations)
+Multi-sample SV calling using Sniffles2 population mode works in two steps:
 
-Arabidopsis trio: 
-+ [http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/Arabidopsis_trio](http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/Arabidopsis_trio) . 
+1. Call SV candidates and create an associated .snf file for each sample: `sniffles2 --input sample1.bam --snf sample1.snf`
+2. Combined calling using multiple .snf files into a single .vcf: `sniffles2 --input sample1.snf sample2.snf ... sampleN.snf --vcf multisample.vcf`
 
-Genome in the Bottle trio: 
-+ Mappings: [ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/AshkenazimTrio/HG002_NA24385_son/PacBio_MtSinai_NIST/Baylor_NGMLR_bam_GRCh37/](ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/AshkenazimTrio/HG002_NA24385_son/PacBio_MtSinai_NIST/Baylor_NGMLR_bam_GRCh37/) . 
+Alternatively, for step 2. you can supply a .tsv file, containing a list of .snf files, and custom sample ids in an optional second column (one sample per line), .e.g.:
+2. Combined calling using a .tsv as sample list: `sniffles2 --input snf_files_list.tsv --vcf multisample.vcf`
 
-+ SV calls: [http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/GiaB/](http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/GiaB/)
+### C. Non-Germline SV Calling (Somatic) 
+To call non-germline SVs (i.e. somatic/mosaic) SVs, the *--non-germline* option should be added, i.e.:
 
-NA12878: 
-+ [http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/NA12878/](http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/NA12878/) .  
+`sniffles --input mapped_input.bam --vcf output.vcf --non-germline`
 
-SKBR3: 
-+ [http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/Skbr3/](http://labshare.cshl.edu/shares/schatzlab/www-data/fsedlaze/Sniffles/Skbr3/) . 
+### D. Genotyping a known set of SVs (Force Calling)
+Example command, to determine the genotype of each SV in *input_known_svs.vcf* for *sample.bam* and write the re-genotyped SVs to *output_genotypes.vcf*:
 
+`sniffles --input sample.bam --genotype-vcf input_known_svs.vcf --vcf output_genotypes.vcf`
+
+## Quick Tips
+
+### Input / Output
+* .bam or .cram files containing long read alignments (i.e. from minimap2 or ngmlr) are supported as input
+* .vcf.gz (bgzipped+tabix indexed) output is supported
+* Simultaneous output of both .vcf and .snf file (for multi-sample calling) is supported