Difference between revisions of "NgsCAT"

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high-throughput sequencing experiments in terms of:
 
high-throughput sequencing experiments in terms of:
  
* Sensitivity, which assesses the quality of the coverage on target regions.
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* Sensitivity, which assesses the quality of the coverage on target regions. It is also important to provide a means of estimating how this coverage
It is also important to provide a means of estimating how this coverage
 
 
would improve by increasing sequencing depth.
 
would improve by increasing sequencing depth.
 
* Specificity, which measures how much of the sequencing effort is wasted on
 
* Specificity, which measures how much of the sequencing effort is wasted on
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==System Variables==
 
==System Variables==
* HPC_{{#uppercase:{{#var:app}}}}_DIR - installation directory
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* HPC_{{uc:{{#var:app}}}}_DIR - installation directory
 
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=Validation=
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* Validated 4/5/2018

Latest revision as of 21:23, 6 December 2019

Description

ngscat website  

ngsCAT (Next Generation Sequencing data Capture Assessment Tool) is a command-line application written in Python which facilitates a comprehensive evaluation of the performance of the capture step in targeted high-throughput sequencing experiments in terms of:

  • Sensitivity, which assesses the quality of the coverage on target regions. It is also important to provide a means of estimating how this coverage

would improve by increasing sequencing depth.

  • Specificity, which measures how much of the sequencing effort is wasted on

sequencing off-target bases.

  • Uniformity, which assesses sequencing biases due to specific genomic

locations or nucleotide composition.

Required Modules

Serial

  • ngscat

System Variables

  • HPC_NGSCAT_DIR - installation directory




Citation

If you publish research that uses ngscat you have to cite it as follows:

Francisco J.López-Domingo, Javier P.Florido, Antonio Rueda, Joaquín Dopazo and Javier Santoyo-López (2014) ngsCAT: a tool to assess the efficiency of targeted enrichment sequencing, Bioinformatics, vol.30, no.12, pp.1767-1768, 2014; doi:10.1093/bioinformatics/btu108.


Validation

  • Validated 4/5/2018