Merge pull request #22 from NBISweden/develop

v2.3

.github/workflows/main.yml

@@ -63,6 +63,9 @@ jobs:
       run: |
         bash .test/scripts/prep_eggnog.sh
         bash .test/scripts/prep_taxonomy.sh
+        mkdir -p results/annotation/emapper-test
+        cp .test/data/emapper-out.tsv results/annotation/emapper-test/emapper-test.emapper.annotations
+        snakemake --config sample_list=.test/config/emapper-test.tsv --use-conda -j 2 --configfile .test/config/annotate.yaml -p results/annotation/emapper-test/{kos,modules,pathways,enzymes}.parsed.tsv
         snakemake --use-conda -j 2 --configfile .test/config/annotate.yaml -p annotate
         rm -r results/assembly examples/data/sample*
     # Test Metabat2 with Megahit (200k reads/sample)

.test/config/emapper-test.tsv

@@ -0,0 +1,2 @@
+sample	unit	assembly	fq1	fq2
+sample1	1	emapper-test	R1	R2

.test/config/kraken.yaml

@@ -224,6 +224,7 @@ kraken:
   # download a prebuilt kraken2 database from the CCB servers
   # choose from "minikraken_8GB","16S_Greengenes","16S_RDP","16S_Silva"
   prebuilt: "16S_Greengenes"
+  prebuilt_url: "https://genome-idx.s3.amazonaws.com/kraken/16S_Greengenes13.5_20200326.tgz"
   # if you already have access to a built kraken database you may specify the
   # database path here (path must contain hash.k2d, opts.k2d and taxo.k2d files
   custom: ""
@@ -241,6 +242,7 @@ centrifuge:
   prebuilt: "p_compressed+h+v"
   # if you already have access to a built centrifuge database you may specify
   # the path to it here.
+  prebuilt_url: ""
   custom: ""
   # minimum score for classifications by centrifuge.
   # because centrifuge doesn't have a filtering algorithm,

.test/data/emapper-out.tsv

@@ -0,0 +1,5 @@
+#query	seed_ortholog	evalue	score	eggNOG_OGs	max_annot_lvl	COG_category	Description	Preferred_name	GOs	EC	KEGG_ko	KEGG_Pathway	KEGG_Module	KEGG_Reaction	KEGG_rclass	BRITE	KEGG_TC	CAZy	BiGG_Reaction	PFAMs
+micpun	296587.XP_002502426.1	3.47e-243	667.0	COG0837@1|root,2QSB1@2759|Eukaryota,37UJV@33090|Viridiplantae,34HS7@3041|Chlorophyta	3041|Chlorophyta	G	Glucokinase	-	-	-	-	-	-	-	-	-	-	-	iRC1080.CRv4_Au5_s1_g1623_t1	Glucokinase
+tr|K4QD32|K4QD32_STREQ	759913.SDSE_1735	7.26e-208	575.0	COG1940@1|root,COG1940@2|Bacteria,1UZ80@1239|Firmicutes,4HD5J@91061|Bacilli,1M9XA@119603|Streptococcus dysgalactiae group	91061|Bacilli	GK	ROK family	ypbG	-	2.7.1.2	ko:K00845	ko00010,ko00052,ko00500,ko00520,ko00521,ko00524,ko01100,ko01110,ko01120,ko01130,ko01200,map00010,map00052,map00500,map00520,map00521,map00524,map01100,map01110,map01120,map01130,map01200	M00001,M00549	R00299,R01600,R01786	RC00002,RC00017	ko00000,ko00001,ko00002,ko01000	-	-	-	ROK
+1000565.METUNv1_03812	1000565.METUNv1_03812	9.6e-207	714.5	COG0012@1|root,COG0012@2|Bacteria,1MVM4@1224|Proteobacteria,2VJ1W@28216|Betaproteobacteria,2KUD2@206389|Rhodocyclales	206389|Rhodocyclales	J	ATPase that binds to both the 70S ribosome and the 50S ribosomal subunit in a nucleotide-independent manner	ychF	-	-	ko:K06942	-	-	-	-	ko00000,ko03009	-	-	-	MMR_HSR1,YchF-GTPase_C
+362663.ECP_0061	362663.ECP_0061	0.0	1624.8	COG0417@1|root,COG0417@2|Bacteria,1MVY9@1224|Proteobacteria,1RMQ1@1236|Gammaproteobacteria,3XPER@561|Escherichia	1236|Gammaproteobacteria	L	DNA polymerase	polB	GO:0003674,GO:0003824,GO:0003887,GO:0004518,GO:0004527,GO:0004529,GO:0004536,GO:0006139,GO:0006259,GO:0006260,GO:0006261,GO:0006281,GO:0006725,GO:0006807,GO:0006950,GO:0006974,GO:0007154,GO:0008150,GO:0008152,GO:0008296,GO:0008408,GO:0009058,GO:0009059,GO:0009432,GO:0009605,GO:0009987,GO:0009991,GO:0016740,GO:0016772,GO:0016779,GO:0016787,GO:0016788,GO:0016796,GO:0016895,GO:0018130,GO:0019438,GO:0031668,GO:0033554,GO:0034061,GO:0034641,GO:0034645,GO:0034654,GO:0043170,GO:0044237,GO:0044238,GO:0044249,GO:0044260,GO:0044271,GO:0045004,GO:0045005,GO:0046483,GO:0050896,GO:0051716,GO:0071496,GO:0071704,GO:0071897,GO:0090304,GO:0090305,GO:0140097,GO:1901360,GO:1901362,GO:1901576	2.7.7.7	ko:K02336	-	-	-	-	ko00000,ko01000,ko03400	-	-	-	DNA_pol_B,DNA_pol_B_exo1

Dockerfile

@@ -9,6 +9,9 @@ SHELL ["/bin/bash", "-c"]
 # Set workdir
 WORKDIR /analysis
 
+# Set tmpdir
+ENV TMPDIR="/scratch"
+
 RUN apt-get update && \
     apt-get install -y --no-install-recommends curl && apt-get clean
 

config/config.yaml

@@ -60,6 +60,9 @@ cutadapt:
   rev_adapter_sequence: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT
   # maximum allowed error rate as value between 0 and 1 (no. of errors divided by length of matching region)
   error_rate: 0.1
+  # extra parameters to pass to cutadapt
+  # for instance you can run cutadapt with quality trimming by specifying "-q 10" here
+  extra_params: ""
 
 # parameters for sortmerna
 sortmerna:
@@ -254,9 +257,10 @@ kraken:
   standard_db: False
   # download a prebuilt kraken2 database from the CCB servers
   # choose from "minikraken_8GB","16S_Greengenes","16S_RDP","16S_Silva"
-  prebuilt: "minikraken_8GB"
+  prebuilt: "Standard-8"
   # if you already have access to a built kraken database you may specify the
   # database path here (path must contain hash.k2d, opts.k2d and taxo.k2d files
+  prebuilt_url: "https://genome-idx.s3.amazonaws.com/kraken/k2_standard_8gb_20200919.tar.gz"
   custom: ""
   # should kraken2 run with reduced memory requirements?
   # setting reduce_memory to True makes kraken2 run in "--memory-mapping" mode
@@ -269,9 +273,10 @@ centrifuge:
   # CCB servers. choose from:
   # "p+h+v", "nt_2018_2_12", "nt_2018_3_3", "p_compressed+h+v" or "p_compressed_2018_4_15"
   # see http://ccb.jhu.edu/software/centrifuge/ for more info
-  prebuilt: "p_compressed+h+v"
+  prebuilt: "refseq-compressed"
   # if you already have access to a built centrifuge database you may specify
   # the path to it here.
+  prebuilt_url: "https://genome-idx.s3.amazonaws.com/centrifuge/p_compressed%2Bh%2Bv.tar.gz"
   custom: ""
   # minimum score for classifications by centrifuge.
   # because centrifuge doesn't have a filtering algorithm,

environment.yml

@@ -7,10 +7,11 @@ channels:
 
 dependencies:
   # core packages for workflow
-  - python=3.7.6
-  - snakemake-minimal=5.18.1
-  - pandas=1.0.1
-  - biopython=1.76
+  - python>=3.7
+  - snakemake-minimal>=5.18
+  - mamba
+  - pandas
+  - biopython
 
   # packages required to create snakemake reports
   - pygments

workflow/Snakefile

@@ -21,13 +21,11 @@ def all_input(wildcards):
     wanted_input = []
 
     if config["run_preprocessing"] or config["preprocessing"]["fastqc"]:
-        wanted_input.append(opj(config["paths"]["results"], "report",
-                                "samples_report.html"))
+        wanted_input.append(results+"/report/samples_report.html")
 
     if config["run_assembly"]:
         # add assembly stats
-        wanted_input.append(opj(config["paths"]["results"], "report",
-                                "assembly", "assembly_stats.pdf"))
+        wanted_input.append(results+"/report/assembly/assembly_stats.pdf")
         # get annotation input
         wanted_input += annotation_input(config, assemblies)
         # get binning input

workflow/envs/annotation.yml

@@ -3,9 +3,9 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python=2.7.15
+  - python=3.7.6
   - prodigal=2.6.3
   - pfam_scan=1.6
-  - eggnog-mapper=2.0.1
+  - eggnog-mapper=2.1.2
   - infernal=1.1.2
   - trnascan-se=2.0.5

workflow/envs/concoct.yml

@@ -6,3 +6,4 @@ dependencies:
   - python=3.7.6
   - biopython=1.76
   - concoct=1.1.0
+  - samtools=1.9

workflow/envs/metabat.yml

@@ -5,3 +5,4 @@ channels:
   - defaults
 dependencies:
   - metabat2=2.14
+  - libdeflate=1.0

workflow/envs/plotting.yml

@@ -4,6 +4,6 @@ channels:
   - defaults
 dependencies:
   - python=3.8.2
-  - seaborn=0.10.1
+  - seaborn=0.11.1
   - pandas=1.0.3
   - jupyter=1.0.0

workflow/envs/preprocess.yml

@@ -10,4 +10,5 @@ dependencies:
   - fastqc=0.11.9
   - multiqc=1.8
   - fastuniq=1.1
-  - bowtie2=2.3.5.1
+  - bowtie2=2.4.1
+  - tbb=2020.3

workflow/envs/quantify.yml

@@ -8,3 +8,4 @@ dependencies:
   - samtools=1.9
   - picard=2.21.9
   - bowtie2=2.4.1
+  - tbb=2020.3