Team III Gene Prediction Group: Difference between revisions

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===[https://github.com/tseemann/barrnap/ '''Barrnap''']===
===[https://github.com/tseemann/barrnap/ '''Barrnap''']===
Barrnap predicts the location of ribosomal RNA genes in genomes by using HMMER 3.1 for HMM searching in RNA:DNA style. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), metazoan mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).
Barrnap predicts the location of ribosomal RNA genes in genomes by using HMMER 3.1 for HMM searching in RNA:DNA style. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), metazoan mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).
=='''Benchmarking of non-coding + results inferred'''==
==='''rRNA Comparison'''===
[[File: RRNA comparison.png|800px|Results: Non-Coding]]
==='''tRNA Comparison'''===
[[File: TRNA comparison.png|800px|Results: Non-Coding]]


=='''Results: Non-Coding'''==
=='''Results: Non-Coding'''==
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* Average of rRNA: 3.34
* Average of rRNA: 3.34
[[File: Infernal team3.png|800px|Results: Non-Coding]]
[[File: Infernal team3.png|800px|Results: Non-Coding]]
=='''Benchmarking of non-coding + results inferred'''==
==='''rRNA Comparison'''===
[[File: RRNA comparison.png|800px|Results: Non-Coding]]
==='''tRNA Comparison'''===
[[File: TRNA comparison.png|800px|Results: Non-Coding]]

Revision as of 20:54, 7 March 2020

Non-Coding homology - Tools

ARAGORN

Aragorn is a computer program identifies tRNA and tmRNA genes. The program employs heuristic algorithms to predict tRNA secondary structure, based on homology with recognized tRNA consensus sequences and ability to form a base-paired cloverleaf. tmRNA genes are identified using a modified version of the BRUCE program.

Infernal

Infernal is for searching DNA sequence databases for RNA structure and sequence similarities. It is an implementation of a special case of profile stochastic context-free grammars called covariance models (CMs). A CM is like a sequence profile, but it scores a combination of sequence consensus and RNA secondary structure consensus, so in many cases, it is more capable of identifying RNA homologs that conserve their secondary structure more than their primary sequence.

Non-Coding Ab initio - Tools

RNAmmer

RNAmmer predicts ribosomal RNA genes in full genome sequences by utilizing two levels of Hidden Markov Models: An initial spotter model searches both strands. The spotter model is constructed from highly conserved loci within a structural alignment of known rRNA sequences.

Barrnap

Barrnap predicts the location of ribosomal RNA genes in genomes by using HMMER 3.1 for HMM searching in RNA:DNA style. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), metazoan mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).

Benchmarking of non-coding + results inferred

rRNA Comparison

Results: Non-Coding

tRNA Comparison

Results: Non-Coding

Results: Non-Coding

Aragorn & RNAmmer

$ aragorn -l -t -gc1 -w input.fasta -fo –o output.fasta
$ aragorn -l -m -gc1 -w input.fasta -fo –o output.fasta
  • Average of tRNA: 40.9
  • Average of tmRNA: 1
  • Average of rRNA: 2.2

Results: Non-Coding

Infernal

$ cmscan --cut_ga --rfam --nohmmonly --tblout $output/$(basename $filename .fasta).tblout --fmt 2 --clanin Rfam.clanin Rfam.cm $filename > $output/$(basename $filename . fasta).cmscan
  • Average of tRNA: 50.5
  • Average of tmRNA: 1
  • Average of rRNA: 3.34

Results: Non-Coding