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updated readme and build_index.sh

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Vasimuddin
2021-11-26 09:53:32 -08:00
committed by Heng Li
parent 249c180b29
commit 23d4edfa31
2 changed files with 13 additions and 8 deletions
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19
README.md
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@@ -2,16 +2,16 @@
### Introduction
mm2-fast is an accelerated implementation of minimap2 on modern CPUs. mm2-fast accelerates all the three major modules of minimap2: (a) seeding, (b) chaining, and (c) pairwise alignment, achieving up to 1.9x speedup and 1.4x speed using AVX512 and AVX2 respectively over minimap2.
mm2-fast is a drop-in replacement of minimap2, providing the same functionality with the exact same output.
In the current version, all the modules are optimized using **AVX-512** vectorization. Detailed benchmark results are available in our [preprint](https://doi.org/10.1101/2021.07.21.453294).
In the current version, all the modules are optimized using **AVX-512** and **AVX2** vectorization. Detailed benchmark results are available in our [preprint](https://doi.org/10.1101/2021.07.21.453294).
### System requirement
Operating System: Linux
mm2-fast was tested using g++ (GCC) 9.2.0 and icpc version 19.1.3.304
Architecture: x86\_64 CPUs with [AVX512](https://en.wikipedia.org/wiki/AVX-512)
Architecture: x86\_64 CPUs with [AVX512][AVX2](https://en.wikipedia.org/wiki/Advanced_Vector_Extensions)
Memory requirement: ~30GB for human genome
### Installation
Clone the *fast-contrib-v2.22* branch from minimap2 github page. The source code can be compiled by simple using *make* command. It only takes a few seconds.
Clone the *fast-contrib-v2.22* branch from minimap2 github page. The source code can be compiled by using *make* command. It only takes a few seconds.
```
git clone --recursive https://github.com/lh3/minimap2.git -b fast-contrib-v2.22 mm2-fast
cd mm2-fast
@@ -25,7 +25,12 @@ The usage of mm2-fast is same as minimap2. Here is an example of mapping ONT rea
```
### Accuracy evaluation
As mm2-fast is an accelerated version of minimap2-v2.22, the output of mm2-fast can be verified against minimap2-v2.22. Note that AVX512-based chaining in mm2-fast by default runs with a chaining parameter *max-chain-skip=infinity* for higher chaining precision. Therefore, for correctness verification, minimap2 should run with a larger value of *max-chain-skip* parameter. Follow the below steps to verify the accuracy of mm2-fast.
As mm2-fast is an accelerated version of minimap2-v2.22, the output of mm2-fast can be verified against minimap2-v2.22. Note that the optimized chaining in mm2-fast is strictly required to be run with a chaining parameter *max-chain-skip=infinity*. Note that having parameter *max-chain-skip=infinity* leads to higher chaining precision. Therefore, for correctness verification, minimap2 should run with a larger value of *max-chain-skip* parameter. Follow the below steps to verify the accuracy of mm2-fast.
```sh
git clone --recursive https://github.com/lh3/minimap2.git -b fast-contrib-v2.22 mm2-fast
cd mm2-fast && make
./minimap2 -ax map-ont test/MT-human.fa test/MT-orang.fa --max-chain-skip=1000000 > mm2-fast_output
```
```sh
git clone https://github.com/lh3/minimap2.git -b v2.22
cd minimap2 && make
@@ -35,14 +40,14 @@ The output generated by minimap2 and mm2-fast should match.
```sh
diff minimap2_output mm2-fast_output > diff_result
```
The file diff\_result should show a clean-diff with the difference of 2 lines, i.e., the lines containing the command-line parameters for minimap2 and mm2-fast.
The file diff\_result should show a clean-diff with the difference of 0 lines.
### Advanced options
The default compilation using make applies two optimizations: AVX512 vectorized chaining and alignment, and learned-indexes based seeding is disabled by default as it requires availability of [Rust](https://en.wikipedia.org/wiki/Rust_(programming_language)). This is because the learned hash-table uses an external training library that runs on Rust. Rust is trivial to install, see https://rustup.rs/ and add its path to .bashrc file. Rust installation only takes a few seconds. Following are the steps to enable learned hash table optimization in mm2-fast:
The default compilation using make applies two optimizations: vectorized chaining and alignment. The learned-indexes based seeding is disabled by default as it requires availability of [Rust](https://en.wikipedia.org/wiki/Rust_(programming_language)). This is because the learned hash-table uses an external training library that runs on Rust. Rust is trivial to install, see https://rustup.rs/ and add its path to .bashrc file. Rust installation only takes a few seconds. Following are the steps to enable learned hash table optimization in mm2-fast:
```sh
# Start by building learned hash table index for optimized seeding module
./build_rmi.sh test/MT-human.fa map-ont ##Takes two arguments: 1. path-to-reference-seq-file 2. preset.
##For human genome, this step should take around 20-30 minutes to finish.
##For human genome, this step should take around 2-3 minutes to finish.
# Next, compile and run the mapping phase
make clean && make lhash=1

2
build_rmi.sh
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@@ -9,7 +9,7 @@ kv_file=$1"_"$2"_minimizers_key_value_sorted"
full_path=`readlink -f $kv_file`
cd ./ext/TAL_offline
cd ./ext/TAL
make lisa_hash
./build-lisa-hash-index $full_path