Raven
Raven is a de novo genome assembler for long uncorrected reads.
Usage
To build raven executable run the following commands:
git clone https://github.com/lbcb-sci/raven && cd raven
cmake -S ./ -B./build -DRAVEN_BUILD_EXE=1 -DCMAKE_BUILD_TYPE=Release
cmake --build build
For faster build times optionally use ninja and enable threading in cmake. Eg.
git clone https://github.com/lbcb-sci/raven && cd raven
cmake -S ./ -B ./build -DRAVEN_BUILD_EXE=1 -DCMAKE_BUILD_TYPE=Release -G Ninja
cmake --build build -j 4
To install the raven executable after build run:
cmake --install ./build
To install python bindings run the following:
pip install git+git://github.com/lbcb-sci/raven.git@master
Python example can be found at PythonLib/example.py
usage: raven [options ...] <sequences> [<sequences> ...]
# default output is to stdout in FASTA format
<sequences>
input file in FASTA/FASTQ format (can be compressed with gzip)
options:
-k, --kmer-len <int>
default: 15
length of minimizers used to find overlaps
-w, --window-len <int>
default: 5
length of sliding window from which minimizers are sampled
-f, --frequency <double>
default: 0.001
threshold for ignoring most frequent minimizers
-i, --identity <double>
default: 0
threshold for overlap between two reads in order to construct an edge between them
if set to zero, this functionality is disabled
-o, --kMaxNumOverlaps <long unsigned int>
default: 32
maximum number of overlaps that will be taken during FindOverlapsAndCreatePiles stage
-p, --polishing-rounds <int>
default: 2
number of times racon is invoked
-m, --match <int>
default: 3
score for matching bases
-n, --mismatch <int>
default: -5
score for mismatching bases
-g, --gap <int>
default: -4
gap penalty (must be negative)
-u, --min-unitig-size <int>
default: 9999
minimal unitig size
--graphical-fragment-assembly <string>
prints the assembly graph in GFA format
--resume
resume previous run from last checkpoint
--disable-checkpoints
disable checkpoint file creation
-t, --threads <int>
default: 1
number of threads
--version
prints the version number
-h, --help
prints the usage
only available when built with CUDA:
-c, --cuda-poa-batches <int>
default: 0
number of batches for CUDA accelerated polishing
-b, --cuda-banded-alignment
use banding approximation for polishing on GPU
(only applicable when -c is used)
-a, --cuda-alignment-batches <int>
default: 0
number of batches for CUDA accelerated alignment
To use raven library component in your project, add the following to your cmake file:
include(FetchContent)
FetchContent_Declare(
raven
GIT_REPOSITORY https://github.com/lbcb-sci/raven
GIT_TAG v1.8.1)
FetchContent_GetProperties(raven)
if (NOT raven_POPULATED)
FetchContent_Populate(raven)
add_subdirectory(
${raven_SOURCE_DIR}
${raven_BINARY_DIR}
EXCLUDE_FROM_ALL)
endif ()
target_link_libraries(<YourTarget> <PRIVATE|PUBLIC|INTERFACE> raven)
Build options
RAVEN_BUILD_TESTS
: build unit testsRAVEN_BUILD_PYTHON
: builds python moduleRAVEN_BUILD_SHARED_LIBS: build raven lib and it's dependencies as shared libraries
RAVEN_BUILD_EXE
: build raven executableracon_enable_cuda
: build with NVIDIA CUDA support
Dependencies
- gcc 7.5+ | clang 8.0+
- cmake 3.11+
- zlib 1.2.8+
Hidden
- pybind11
- lbcb-sci/racon/tree/library 3.0.2
- rvaser/bioparser 3.0.13
- (raven_test) google/googletest 1.10.0
Other options
NOTE: not updated for 1.8 release
Brew
Install Linuxbrew and run the following command:
brew install brewsci/bio/raven-assembler
Conda
Install conda and run the following command:
conda install -c bioconda raven-assembler
Acknowledgment
This work has been supported in part by the Genome Institute of Singapore (A*STAR), by the Croatian Science Foundation under projects Algorithms for genome sequence analysis (UIP-11-2013-7353) and Single genome and metagenome assembly (IP-2018-01-5886), and in part by the European Regional Development Fund under grant KK.01.1.1.01.0009 (DATACROSS).