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Taxonomic profiling with the GTDB‐R214 database
In this tutorial, we will use sylph to do
- Multi-sample prokaryotic metagenomic profiling with the GTDB-R214 database
- output a taxonomic output like MetaPhlAn.
- sylph is installed.
Note
This tutorial uses the GTDB-R214 database, an older database. A new GTDB version (R220) has 35% more genomes. Refer to the pre-built databases.
Download the pre-sketched (i.e., indexed) GTDB-R214 database provided here. For example,
wget https://storage.googleapis.com/sylph-stuff/v0.3-c1000-gtdb-r214.syldb -O gtdb_database.syldb
# OR
#wget https://storage.googleapis.com/sylph-stuff/v0.3-c200-gtdb-r214.syldb -O gtdb_database.syldb
- The
c1000database is smaller and faster, but less sensitive for low-abundance genomes compared to thec200database.
Assuming you have the GTDB-R214 genome database present in a folder called gtdb_genomes_reps_r214/, do the following:
- Compile all GTDB genomes into a list file:
find gtdb_genomes_reps_r214 | grep .fna > gtdb_all.txt - Create a database with:
sylph sketch -l gtdb_all.txt -t 50 -o gtdb_database
Let's download and index two mouse gut metagenomes:
wget https://storage.googleapis.com/sylph-stuff/mouse_1.fq.gz
wget https://storage.googleapis.com/sylph-stuff/B-mouse_1.fq.gz
wget https://storage.googleapis.com/sylph-stuff/mouse_2.fq.gz
wget https://storage.googleapis.com/sylph-stuff/B-mouse_2.fq.gz
We now have two sets of paired-reads. For paired-end reads, sylph must sketch the reads first as follows:
sylph sketch -1 *mouse_1.fq.gz -2 *mouse_2.fq.gz sylph can sketch multiple samples at once. This allows for multi-threaded sketching and is more efficient.
This outputs two files called mouse_1.fq.gz.paired.sylsp and B-mouse_1.fq.gz.paired.sylsp. The paired indicates the sketch was created with the -1,-2 options, and the sylsp indicates that it is indexed.
Caution
Do not interleave paired-end reads. Sylph will give more accurate results if you do not concatenate/interleave your reads.
To multi-sample profile with sylph, run the following:
sylph profile gtdb_database.syldb *mouse_1.fq.gz.paired.sylsp -t 10 -o results.tsvThis uses 10 threads to profile the metagenome against our database into a file called results.tsv.
Tip
Since sylph v0.6, direct profiling of paired-end reads without sketching is possible:
sylph profile gtdb_database.syldb -1 *_1.fq.gz -2 *_2.fq.gz -t 10 -o results.tsvInspecting the results.tsv file gives:
head results.tsv
Sample_file Genome_file Taxonomic_abundance Sequence_abundance Adjusted_ANI Eff_cov ANI_5-95_percentile Eff_lambda Lambda_5-95_percentile Median_cov Mean_cov_geq1 Containment_ind Naive_ANI Contig_name
mouse_1.fq gtdb_genomes_reps_r214/database/GCA/910/577/315/GCA_910577315.1_genomic.fna.gz 10.6258 10.1684 97.66 0.656 97.33-98.07 0.656 0.55-0.76 1 1.456 616/2624 95.43 CAJTME010000001.1 TPA_asm: uncultured Muribaculaceae bacterium isolate MGBC104416 genome assembly, contig: MGBC104416.1, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCF/001/945/605/GCF_001945605.1_genomic.fna.gz 9.1588 7.5114 98.36 0.565 97.92-98.84 0.565 0.47-0.66 1 1.421 553/2100 95.79 NZ_MPKA01000006.1 Dubosiella newyorkensis strain NYU-BL-A4 NODE_100_length_1023_cov_1250.21_ID_199, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCA/910/589/675/GCA_910589675.1_genomic.fna.gz 8.3282 5.1014 95.18 0.514 94.47-95.99 0.514 0.37-0.67 1 1.299 144/1629 92.47 CAJUTO010000001.1 uncultured Lactobacillus sp. isolate MGBC166701 genome assembly, contig: MGBC166701.1, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCA/910/588/855/GCA_910588855.1_genomic.fna.gz 8.1294 11.9822 98.20 0.502 97.87-98.59 0.502 0.43-0.56 1 1.345 892/3903 95.35 CAJUSR010000001.1 TPA_asm: uncultured Kineothrix sp. isolate MGBC162921 genome assembly, contig: MGBC162921.1, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCA/910/579/675/GCA_910579675.1_genomic.fna.gz 7.7809 7.5080 98.71 0.480 98.27-99.11 0.480 0.40-0.55 1 1.303 654/2522 95.74 CAJTUF010000001.1 TPA_asm: uncultured Muribaculaceae bacterium isolate MGBC114255 genome assembly, contig: MGBC114255.1, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCF/001/591/705/GCF_001591705.1_genomic.fna.gz 7.1538 6.0999 96.41 0.441 95.86-97.20 0.441 0.32-0.54 1 1.216 264/2258 93.31 NZ_BCVK01000001.1 Lactococcus lactis subsp. cremoris NBRC 100676, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCF/000/403/395/GCF_000403395.2_genomic.fna.gz 6.9472 9.1490 95.75 0.429 95.27-96.45 0.429 0.32-0.51 1 1.251 299/3240 92.60 NZ_KE159657.1 Anaerotruncus sp. G3(2012) strain G3 acPFl-supercont1.1, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCA/003/833/075/GCA_003833075.1_genomic.fna.gz 5.7036 7.2196 97.02 0.352 96.46-97.75 0.352 0.27-0.42 1 1.234 394/3324 93.35 RIAY01000001.1 Muribaculaceae bacterium Isolate-036 (Harlan) seq1, whole genome shotgun sequence
mouse_1.fq gtdb_genomes_reps_r214/database/GCA/910/587/685/GCA_910587685.1_genomic.fna.gz 5.0394 3.2464 97.82 0.311 97.06-98.58 0.311 0.24-0.39 1 1.200 230/1672 93.80 CAJUMY010000001.1 TPA_asm: uncultured Christensenellaceae bacterium isolate MGBC161649 genome assembly, contig: MGBC161649.1, whole genome shotgun sequence
You can check https://github.com/bluenote-1577/sylph/wiki/Output-format for the definitions of each of the columns.
Sylph's TSV output has no taxonomic information, only genome information. To get a taxonomic profile, we integrate GTDB's taxonomy with sylph's output. See here for more information.
Run the following commands:
conda install -c bioconda sylph-tax
# only have to do this once
mkdir taxonomy_file_folder
sylph-tax download --download-to taxonomy_file_folder
sylph-tax taxprof results.tsv -t GTDB_r214 -o prefix_
ls prefix_mouse_1.fq.gz.sylphmpa
ls prefix_B-mouse_2.fq.gz.sylphmpaImportant
-t's metadata file must correspond to database used. See sylph-tax for available database. If you use GTDB-R220 or R214, you must use the correct R220 or R214 taxonomy.
The script outputs a new file called prefix_MYSAMPLENAME.sylphmpa for each sample in the results file. Investigating one file gives the following:
head -n 20 prefix_mouse_1.fq.sylphmpa
#SampleID mouse_1.fq
clade_name relative_abundance sequence_abundance ANI (if strain-level)
d__Bacteria 100.00010000000002 99.99999999999999 NA
d__Bacteria|p__Bacillota 24.640800000000002 18.712699999999998 NA
d__Bacteria|p__Bacillota_A 47.333499999999994 52.5969 NA
d__Bacteria|p__Bacillota_A|c__Clostridia 47.333499999999994 52.5969 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales 9.0019 6.252800000000001 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__Pumilibacteraceae 3.9625 3.0064 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__Pumilibacteraceae|g__Pumilibacter 3.9625 3.0064 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__Pumilibacteraceae|g__Pumilibacter|s__Pumilibacter 3.9625 3.0064 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__Pumilibacteraceae|g__Pumilibacter|s__Pumilibacter|t__GCA_910587595.1 3.9625 3.0064 95.45
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__UBA3700 5.0394 3.2464 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__UBA3700|g__MGBC161649 5.0394 3.2464 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__UBA3700|g__MGBC161649|s__MGBC161649 5.0394 3.2464 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Christensenellales|f__UBA3700|g__MGBC161649|s__MGBC161649|t__GCA_910587685.1 5.0394 3.2464 97.82
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Lachnospirales 20.3153 24.426900000000003 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Lachnospirales|f__Lachnospiraceae 20.3153 24.426900000000003 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Lachnospirales|f__Lachnospiraceae|g__1XD42-69 4.1703 4.1626 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Lachnospirales|f__Lachnospiraceae|g__1XD42-69|s__1XD42-69 4.1703 4.1626 NA
d__Bacteria|p__Bacillota_A|c__Clostridia|o__Lachnospirales|f__Lachnospiraceae|g__1XD42-69|s__1XD42-69|t__GCA_910589105.1 4.1703 4.1626 97.47
This file is a taxonomic profile similar to what MetaPhlAn outputs. Each taxonomic rank has an associated taxonomic or sequence abundance.
Note
Taxonomic abundance normalizes by genome sizes, whereas sequence abundance is the % of reads assigned to a taxonomic rank. See Sun et al., 2021 for information.
Note that the t__GCA_... ranks, which are strain/genome-level ranks, have an associated ANI output. The other ranks do not.
We have just shown how sylph can do multi-sample profiling against the GTDB-R214 database very efficiently while giving ANI information as well.
To do taxonomic profiling with other databases, see the manual. Alternatively, consider just analyzing sylph's resulting TSV file; it contains some useful information not present in the taxonomic profile.