Custom version of BLAST for textreuse detection.
These are modifications to BLAST source code originally made by Aleksi Vesanto (https://github.com/avjves) for the purpose of text reuse detection. They have been ported over to a later version of BLAST, which was made necessary by later GCC compilers refusing to compile the original modified source.
The sourcecode has to be compiled so it will run in which ever environment you are running locally / on a cluster:
cd ncbi-blast-2.13.0+-src_modified/c++ ## Now inside the BLAST source directory
./configure ## Run configure file
make ## Compile the program
Binary files are now in in ncbi-blast-2.13.0+-src_modified/c++/ReleaseMT/bin
The software expects BLAST binaries to be in PATH. This can be done by:
export PATH="/path/to/ncbi-blast-2.13.0+-src_modified/c++/ReleaseMT/bin:$PATH"
This should most likely be added to your .bashrc file, so it remains in different sessions as well.
Compared to standard BLAST, the following two modifications have been made:
/src/algo/blast/core/blast_stat.chas a line (line 270 in 2.13.0 source) changed in BLOSUM62_VALUES_MAX to match the gap_open and gap_extend values needed for ECCO. The new line is as follows:{3, 11, (double) INT2_MAX, 0.201, 0.012, 0.061, 3.3, -58, 0.740802, 140.417000, 141.882000},- The BLOSUM scoring matrix in
/src/util/tables/sm_blosum62.chas been rewritten to be uniform.
The modified files can be found in /modifications
GPU BLAST might be one solution to the speed problems with BLAST and ECCO. There are a few implementations, but none have been updated in a while:
- Heterogeneous BLAST (H-BLAST): https://github.com/Yeyke/H-BLAST , https://academic.oup.com/bioinformatics/article/33/8/1130/2900493
- Claims to be 1.5–4 times faster than GPU-BLAST. Combines GPU and CPU threads.
- GPU-Blast: https://sahinidis.coe.gatech.edu/gpublast
- cuBLASTP: https://github.com/vtsynergy/cuBLASTP , https://ieeexplore.ieee.org/document/6877260
- Claims to be 2.8 times faster than GPU-BLASTP
Articles:
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3018811/
- More recent one listing GPU implementations of BLAST: https://link.springer.com/article/10.1007/s11227-020-03267-1
- An Analysis of BLASTP Implementation on NVIDIA GPUs http://biochem218.stanford.edu/Projects%202012/Glasco.pdf