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SPDE: A Multi-functional Software for Sequence Processing and Data Extraction
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Abstract
Efficiently extracting information from biological big data can be a huge challenge for people (especially those who lack programming skills). We developed
S
equence
P
rocessing and
D
ata
E
xtraction (SPDE) as an integrated tool for sequence processing and data extraction for gene family and omics analyses. Currently, SPDE has seven modules comprising 100 basic functions that range from single gene processing (e.g., translation, reverse complement, and primer design) to genome information extraction. All SPDE functions can be used without the need for programming or command lines. The SPDE interface has enough prompt information to help users run SPDE without barriers. In addition to its own functions, SPDE also incorporates the publicly available analyses tools (such as, NCBI-blast, HMMER, Primer3 and SAMtools), thereby making SPDE a comprehensive bioinformatics platform for big biological data analysis.
Availability
SPDE was built using Python and can be run on 32-bit, 64-bit Windows and macOS systems. It is an open-source software that can be downloaded from
https://github.com/simon19891216/SPDEv1.2.git
.
Contact
xudongzhuanyong@163.com
Title: SPDE: A Multi-functional Software for Sequence Processing and Data Extraction
Description:
Abstract
Efficiently extracting information from biological big data can be a huge challenge for people (especially those who lack programming skills).
We developed
S
equence
P
rocessing and
D
ata
E
xtraction (SPDE) as an integrated tool for sequence processing and data extraction for gene family and omics analyses.
Currently, SPDE has seven modules comprising 100 basic functions that range from single gene processing (e.
g.
, translation, reverse complement, and primer design) to genome information extraction.
All SPDE functions can be used without the need for programming or command lines.
The SPDE interface has enough prompt information to help users run SPDE without barriers.
In addition to its own functions, SPDE also incorporates the publicly available analyses tools (such as, NCBI-blast, HMMER, Primer3 and SAMtools), thereby making SPDE a comprehensive bioinformatics platform for big biological data analysis.
Availability
SPDE was built using Python and can be run on 32-bit, 64-bit Windows and macOS systems.
It is an open-source software that can be downloaded from
https://github.
com/simon19891216/SPDEv1.
2.
git
.
Contact
xudongzhuanyong@163.
com.
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