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ADRes: a computational pipeline for detecting molecular markers of Anti-malarial Drug Resistance, from Sanger sequencing data
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Abstract
Background
Malaria control efforts are stifled by the emergence and dispersal of parasite strains resistant to available anti-malarials. Amino acid changes in specific positions of proteins encoded by
Plasmodium falciparum
genes
pfcrt, dhps, dhfr
, and
pfmdr1
are used as molecular markers of resistance to antimalarials such as chloroquine, sulphadoxine-pyrimethamine, as well as artemisinin derivatives. However, a challenge to the detection of single nucleotide polymorphisms (SNPs) in codons responsible for these amino acid changes, in several samples, is the scarcity of automated computational pipelines for molecular biologists to; rapidly analyze ABI (Applied Biosystems) Sanger sequencing data spanning the codons of interest in order to characterize these codons and detect these molecular markers of drug resistance. The pipeline described here is an attempt to address this need.
Method
This pipeline is a combination of existing tools, notably SAMtools and Burrows Wheeler Aligner (BWA), as well as custom Python and BASH scripts. It is designed to run on the UNIX shell, a command line interpreter. To characterize the codons associated with anti-malarial drug resistance (ADR) in a particular gene using this pipeline, the following options are required; a path to reference coding sequence of the gene in FASTA format, gene symbol (pfcrt, pfmdr1, dhps or dhfr), and a path to the directory of ABI sequencing trace files for the samples. With these inputs, the pipeline performs base calling and trimming, sequence alignment, and alignment parsing.
Results
The output of the pipeline is a CSV (Comma-separated values) file of sample names, codons and their corresponding encoded amino acids. The data generated can be readily analyzed using widely available statistical or spreadsheet software, to determine the frequency of molecular markers of resistance to anti-malarials such as chloroquine, sulphadoxine-pyrimethamine and artemisinin derivatives.
Conclusions
ADRes is a quick and effective pipeline for detecting common molecular markers of anti-malarial drug resistance, and could be a useful tool for surveillance. The code, description, and instructions for using this pipeline are publicly available at
http://setfelix.github.io/ADRes
.
Title: ADRes: a computational pipeline for detecting molecular markers of Anti-malarial Drug Resistance, from Sanger sequencing data
Description:
Abstract
Background
Malaria control efforts are stifled by the emergence and dispersal of parasite strains resistant to available anti-malarials.
Amino acid changes in specific positions of proteins encoded by
Plasmodium falciparum
genes
pfcrt, dhps, dhfr
, and
pfmdr1
are used as molecular markers of resistance to antimalarials such as chloroquine, sulphadoxine-pyrimethamine, as well as artemisinin derivatives.
However, a challenge to the detection of single nucleotide polymorphisms (SNPs) in codons responsible for these amino acid changes, in several samples, is the scarcity of automated computational pipelines for molecular biologists to; rapidly analyze ABI (Applied Biosystems) Sanger sequencing data spanning the codons of interest in order to characterize these codons and detect these molecular markers of drug resistance.
The pipeline described here is an attempt to address this need.
Method
This pipeline is a combination of existing tools, notably SAMtools and Burrows Wheeler Aligner (BWA), as well as custom Python and BASH scripts.
It is designed to run on the UNIX shell, a command line interpreter.
To characterize the codons associated with anti-malarial drug resistance (ADR) in a particular gene using this pipeline, the following options are required; a path to reference coding sequence of the gene in FASTA format, gene symbol (pfcrt, pfmdr1, dhps or dhfr), and a path to the directory of ABI sequencing trace files for the samples.
With these inputs, the pipeline performs base calling and trimming, sequence alignment, and alignment parsing.
Results
The output of the pipeline is a CSV (Comma-separated values) file of sample names, codons and their corresponding encoded amino acids.
The data generated can be readily analyzed using widely available statistical or spreadsheet software, to determine the frequency of molecular markers of resistance to anti-malarials such as chloroquine, sulphadoxine-pyrimethamine and artemisinin derivatives.
Conclusions
ADRes is a quick and effective pipeline for detecting common molecular markers of anti-malarial drug resistance, and could be a useful tool for surveillance.
The code, description, and instructions for using this pipeline are publicly available at
http://setfelix.
github.
io/ADRes
.
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