Team III Functional Annotation Group: Difference between revisions
No edit summary |
Arozanski3 (talk | contribs) No edit summary |
||
Line 6: | Line 6: | ||
[[File: Init pipeline.PNG]] | [[File: Init pipeline.PNG]] | ||
=='''Clustering'''== | |||
=='''USEARCH'''== | |||
We chose to cluster the genes based upon similarity in order to reduce the amount of overlap when annotating these genes. This is executed through the UCLUST algorithm. UCLUST preforms this by creating clusters that contain a single centroid sequence upon which the other sequences must have a certain sequence similarity to be considered apart of the cluster. We can set an identity threshold which can be thought of as the radius of the cluster. | |||
For our analysis we decided to use an identity threshold of 97% because we obtained larger average cluster sizes and relatively low amount of singletons 1% | |||
=='''Homology Tools'''== | =='''Homology Tools'''== | ||
=='''eggNOG mapper'''== | |||
eggNOG-mapper is a Tool for functional assignments based on precomputed orthologous clusters present it the eggNOG database. This is performed in the steps as follows | |||
1) Sequence Mapping using HMMER3 or DIAMOND, for our analyses we use DIAMOND as a result of size of input and as because it is recommended over HMMER3 when annotating organisms with close relatives among the species covered by eggNOG | |||
2)Orthology assignment | |||
3)Functional Annotation, which is restricted to closest orthologs for reduction of false positives | |||
===[https://card.mcmaster.ca/analyze/rgi '''CARD-RGI''']=== | ===[https://card.mcmaster.ca/analyze/rgi '''CARD-RGI''']=== |
Revision as of 21:17, 9 April 2020
Group Members - Allison, Bengu, Cheng, Pallavi Misra
Introduction
Initial Pipeline
Clustering
USEARCH
We chose to cluster the genes based upon similarity in order to reduce the amount of overlap when annotating these genes. This is executed through the UCLUST algorithm. UCLUST preforms this by creating clusters that contain a single centroid sequence upon which the other sequences must have a certain sequence similarity to be considered apart of the cluster. We can set an identity threshold which can be thought of as the radius of the cluster.
For our analysis we decided to use an identity threshold of 97% because we obtained larger average cluster sizes and relatively low amount of singletons 1%
Homology Tools
eggNOG mapper
eggNOG-mapper is a Tool for functional assignments based on precomputed orthologous clusters present it the eggNOG database. This is performed in the steps as follows
1) Sequence Mapping using HMMER3 or DIAMOND, for our analyses we use DIAMOND as a result of size of input and as because it is recommended over HMMER3 when annotating organisms with close relatives among the species covered by eggNOG
2)Orthology assignment
3)Functional Annotation, which is restricted to closest orthologs for reduction of false positives
CARD-RGI
Comprehensive Antibiotic Resistance Database (CARD) is a rigorously curated collection of characterized, peer-reviewed Antibiotic Resistance Genes which is monthly updated. Resistance Gene Identifier(RGI) is a toolkit based on CARD for annotating Antimicrobial genes.
VFDB
Virulence Factor Database (VFDB) is an integrated and comprehensive online resource for curating information about virulence factors of bacterial pathogens (recently updated in 2019). The database contains information such as structure features of the virulence factors, functions and mechanisms used by the pathogens for circumventing host defense mechanisms and causing pathogenicity. Core dataset of DNA sequences was downloaded from VFDB website, which include genes associated with experimentally verified Virulence Factors only. BLAST database was build based on the downloaded dataset from VFDB and BLASTN was used.
Ab-initio Tools
PILERCR
CRISPR are family of DNA sequences found in the genomes of prokaryotic organisms- bacteria and archaea. They are derived from DNA fragments of viruses that had previously infected the prokaryote and provides protection from viruses and plays a major role in antiviral defense system. PILERCR identifies CRISPR repeats by using BLAST to find their fragmented/ degraded copies. A CRISPR array is found when it fulfills the criteria of having a set of CRISPR repeats with intervening unique sequences known as spacers. This program provides fast identification and classification of CRISPR genes and also has both high sensitivity and high specificity.
Final Pipeline
Results
CARD-RGI
$ rgi -i <input_file> -o <output_file>
VFDB
$ makeblastdb -in <input_db> -parse_seqids -blastdb_version 5 -dbtype nucl -out <name_db> $ blastn -db <name_db> -query <input_file> -out <output_file> -max_hsps 1 -max_target_seqs 1 -num_threads 4 -evalue 1e-5
PILERCR
$ ./pilercr -in <input_file> -out <output_file>
References
Barrangou R. The roles of CRISPR-Cas systems in adaptive immunity and beyond. Curr Opin Immunol. 2015;32:36–41. doi:10.1016/j.coi.2014.12.008
Edgar, Robert C. "PILER-CR: fast and accurate identification of CRISPR repeats." BMC bioinformatics 8.1 (2007): 18.
Alcock, Brian P., et al. "CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database." Nucleic acids research 48.D1 (2020): D517-D525.
Liu, Bo, et al. "VFDB 2019: a comparative pathogenomic platform with an interactive web interface." Nucleic acids research 47.D1 (2019): D687-D692.