Raven is a de novo genome assembler for long uncorrected reads.
To build raven run the following commands (< 30s):
git clone https://github.com/lbcb-sci/raven && cd raven && mkdir build && cd build
cmake -DCMAKE_BUILD_TYPE=Release .. && make
which will create raven executable and unit tests (running make install
will install the executable to your system). Running the executable will display the following usage:
usage: raven [options ...] <sequences>
# default output is to stdout in FASTA format
<sequences>
input file in FASTA/FASTQ format (can be compressed with gzip)
options:
--weaken
use larger (k, w) when assembling highly accurate sequences
-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)
--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
raven_build_tests
: build unit testsracon_enable_cuda
: build with NVICIDA CUDA support
- gcc 4.8+ | clang 4.0+
- cmake 3.11+
- zlib 1.2.8+
Hidden
- lbcb-sci/racon/tree/library 3.0.1
- rvaser/bioparser 3.0.13
- (racon_test) google/googletest 1.10.0
Install Linuxbrew and run the following command:
brew install brewsci/bio/raven-assember
Install conda and run the following command:
conda install -c bioconda raven-assembler
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).