metacache | memory efficient , fast & precise taxnomomic classification | Genomics library
kandi X-RAY | metacache Summary
kandi X-RAY | metacache Summary
MetaCache is a classification system for mapping genomic sequences (short reads, long reads, contigs, ...) from metagenomic samples to their most likely taxon of origin. MetaCache aims to reduce the memory requirement usually associated with k-mer based methods while retaining their speed. It uses locality sensitive hashing to quickly identify candidate regions within one or multiple reference genomes. A read is then classified based on the similarity to those regions. For an independend comparison to other tools in terms of classification accuracy see the LEMMI benchmarking site. MetaCache's CPU version classifies around 60 Million reads (of length 100) per minute against all complete bacterial, viral and archaea genomes from NCBI RefSeq Release 97 running with 88 threads on a workstation with 2 Intel(R) Xeon(R) Gold 6238 CPUs. MetaCache's GPU version classifies around 300 Million reads (of length 100) per minute against all complete bacterial, viral, fungal and archaea genomes from NCBI RefSeq Release 202 running on a workstation with 4 NVIDIA(R) Tesla(R) V100 GPUs (32 GB model). MetaCache-GPU will be presented at ICPP '21.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of metacache
metacache Key Features
metacache Examples and Code Snippets
Lines of Code : 9License : Strong Copyleft (GPL-3.0)
Copysudo apt install -y zlib1g zlib1g-dev
git clone https://github.com/muellan/metacache.git
cd metacache
make
./metacache-build-refseq
./metacache query refseq myReads.fa -out results.txt
./metacache query refseq anyFolderWithFastaOrFastqFiles -out res ./metacache help
./metacache help build
./metacache help query
...
sudo apt install -y zlib1g zlib1g-dev
make MC_ZLIB=NO
Community Discussions
Trending Discussions on Genomics
QUESTION
I´m working with two text files that look like this: File 1
...ANSWER
Answered 2022-Apr-09 at 00:49Perhaps you are after this?
QUESTION
I'm using the software plink2 (https://www.cog-genomics.org/plink/2.0/) and I'm trying to iterate over 3 variables.
This software admits an input file with .ped extention file and an exclude file with .txt extention which contains a list of names to be excluded from the input file.
The idea is to iterate over the input files and then over exclude files to generate single outputfiles.
- Input files: Highland.ped - Midland.ped - Lowland.ped
- Exclude-map files: HighlandMidland.txt - HighlandLowland.txt - MidlandLowland.txt
- Output files: HighlandMidland - HighlandLowland - MidlandHighland - MidlandLowland - LowlandHighland - LowlandMidland
The general code is:
...ANSWER
Answered 2021-Dec-09 at 23:50Honestly, I think your current code is quite clear; but if you really want to write this as a loop, here's one possibility:
QUESTION
From this example string:
...ANSWER
Answered 2021-Dec-09 at 01:11use regexp_extract(col, r"&q;Stockcode&q;:([^/$]*?),&q;.*")
if applied to sample data in your question - output is
QUESTION
I am making a code which takes in jumble word and returns a unjumbled word , the data.json contains a list and here take a word one-by-one and check if it contains all the characters of the word and later checking if the length is same , but the problem is when i enter a word as helol then the l is checked twice and giving me some other outputs including the main one(hello). i know why does it happen but i cant get a fix to it
...ANSWER
Answered 2021-Nov-25 at 18:33As I understand it you are trying to identify all possible matches for the jumbled string in your list. You could sort the letters in the jumbled word and match the resulting list against sorted lists of the words in your data file.
QUESTION
I am trying to use plink1.9 to split multiallelic into biallelic. The input is that
...ANSWER
Answered 2021-Nov-17 at 09:45I used bcftools to complete the task.
QUESTION
I have a FASTA file that has about 300000 sequences but some of the sequences are like these
...ANSWER
Answered 2021-Oct-12 at 20:28You can match your non-X containing FASTA entries with the regex >.+\n[^X]+\n. This checks for a substring starting with > having a first line of anything (the FASTA header), which is followed by characters not containing an X until you reach a line break.
For example:
QUESTION
For example, I have two strings:
...ANSWER
Answered 2021-Oct-04 at 22:27For your example your pattern would be:
QUESTION
I am currently trying to run genomic analyses pipelines using Hail(library for genomics analyses written in python and Scala). Recently, Apache Spark 3 was released and it supported GPU usage.
I tried spark-rapids library start an on-premise slurm cluster with gpu nodes. I was able to initialise the cluster. However, when I tried running hail tasks, the executors keep getting killed.
On querying in Hail forum, I got the response that
That’s a GPU code generator for Spark-SQL, and Hail doesn’t use any Spark-SQL interfaces, only the RDD interfaces.
So, does Spark3 not support GPU usage for RDD interfaces?
...ANSWER
Answered 2021-Sep-23 at 05:53As of now, spark-rapids doesn't support GPU usage for RDD interfaces.
Source: Link
Apache Spark 3.0+ lets users provide a plugin that can replace the backend for SQL and DataFrame operations. This requires no API changes from the user. The plugin will replace SQL operations it supports with GPU accelerated versions. If an operation is not supported it will fall back to using the Spark CPU version. Note that the plugin cannot accelerate operations that manipulate RDDs directly.
Here, an answer from spark-rapids team
Source: Link
We do not support running the RDD API on GPUs at this time. We only support the SQL/Dataframe API, and even then only a subset of the operators. This is because we are translating individual Catalyst operators into GPU enabled equivalent operators. I would love to be able to support the RDD API, but that would require us to be able to take arbitrary java, scala, and python code and run it on the GPU. We are investigating ways to try to accomplish some of this, but right now it is very difficult to do. That is especially true for libraries like Hail, which use python as an API, but the data analysis is done in C/C++.
QUESTION
I have 1500 files with the same format (the .scount file format from PLINK2 https://www.cog-genomics.org/plink/2.0/formats#scount), an example is below:
...ANSWER
Answered 2021-Sep-07 at 11:10a tidyverse solution
QUESTION
I have been implementing a suite of RecordBatchReaders for a genomics toolset. The standard unit of work is a RecordBatch. I ended up implementing a lot of my own compression and IO tools instead of using the existing utilities in the arrow cpp platform because I was confused about them. Are there any clear examples of using the existing compression and file IO utilities to simply get a file stream that inflates standard zlib data? Also, an object diagram for the cpp platform would be helpful in ramping up.
...ANSWER
Answered 2021-Jun-02 at 18:58Here is an example program that inflates a compressed zlib file and reads it as CSV.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install metacache
install the zlib library
download the MetaCache source code from GitHub
compile MetaCache (without GPU support)
download the complete bacterial, viral and archaea genomes from the latest NCBI RefSeq release (this can take some time)
build a classification database
Visit MetaCache's github repository to get the latest resources.
To compile the CPU version: run make in the directory containing the Makefile
To compile the GPU version, follow the instructions provided here.
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