What is the difference between Greengenes and SILVA?

Dear Sir,

Thank you for your support. It took me to 12 hours to set my classifier(Greengenes99%OTS) the recent one. I used the commands that you have sent to me. Every thing is fine now. Finally I got ref.seqs.qza file. I have a final question what is the difference between Greengenes99% and Silva123 and 128 databases. Will they give information upto species level? Some say you should choose Silva and some say you should choose Greengenes? Could you elaborate? I would be thankful.

With best regards,

Aqleem Abbas

Hi @Aqleem12!

Greengenes is a 16S/Archaea database and SILVA is a 16S/18S/Archaea database. SILVA also has 23S/28S databases but I’m not sure if those are in a QIIME-compatible format. You can find a list of QIIME-compatible reference databases on the data resources page.

SILVA 123 and 128 are different versions of the SILVA database. In general, you’ll want to keep up-to-date with the latest versions of your reference database of choice.

Both Greengenes and SILVA databases contain reference taxonomies that include species-level annotations. However, you may or may not get species-level classifications of your data depending on the feature-classification algorithm (and parameter configurations) you choose. This preprint benchmarks different feature classification algorithms and parameter configurations, and provides some recommendations for classifier/parameter choices.

There isn’t a yes/no answer here for which reference database to choose. Each database has its strengths and limitations, and every reference database has inherent flaws (there is no “correct” database).

Each person you talk to will have their own opinions and preferred reference database. I encourage you to reach out to the colleagues you mentioned to find out why they prefer one over the other.

Some factors that come to mind:

  • You may have to choose one database over another depending on the marker gene you’re targeting. For example, if you have 18S data, Greengenes wouldn’t be an option because it’s a 16S database.

  • Size of the reference database. SILVA is larger than Greengenes, which can require more CPU time and memory to use, with the benefit of having more reference data.

  • Database updates. SILVA provides fairly regular updates (i.e. new versions) of its database, while the last Greengenes release was August 2013.

  • Techniques used to construct the databases. This is where you’ll need to do some digging – how are the reference databases constructed, and do you prefer/trust one method over another?

I also recommend checking out the official Greengenes and SILVA websites, along with their associated publications, as you make this decision. Finally, if this is an option for you, try out both databases and compare your results!

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Dear Sir,

Thank you for helping me. I have finally got Silva128 ref-seqs.qza files. It took me approximately 20 hours. My conclusion is that Greengenes 13.8 version takes less time as compared to Silva128 versions. I got the required files by using both databases. Silva128 (99%) as well as Greengenes13.8 99% databases. For your information I use both the following commands and results were surprising. Both the commands are giving me the taxonomy. qzv file. However when I use -p-trun len 300 option some of the notations i.e. g_____ and s______ were missing. If I donot use -p-trun len 300 then there were g____ and s___ notations. More Surprisingly the size of the resultant file taxonomy.qzv was same. You may see the following commands and the taxonomy.qzv file .

qiime feature-classifier extract-reads
--i-sequences 99_otus.qza
--p-f-primer CCTACGGRRBGCASCAGKVRVGAAT
--p-r-primer GGACTACNVGGGTWTCTAATCC
--p-trunc-len 300
--o-reads ref-seqs.qza

qiime feature-classifier extract-reads
--i-sequences 99_otus.qza
--p-f-primer CCTACGGRRBGCASCAGKVRVGAAT
--p-r-primer GGACTACNVGGGTWTCTAATCC
--o-reads ref-seqs.qza

@Aqleem12 can you please create a new forum topic with your latest questions? We try to keep each forum thread focused on a single topic. Thanks!

Dear Sir,

Thanks for your reply! I will create new topic.

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