I get a MissingInputException when I run the following rule:
configfile: "Configs.yaml"
rule download_data_from_ZFIN:
input:
anatomy_item = config["ZFIN_url"]["anatomy_item"],
xpat_stage_anatomy = config["ZFIN_url"]["xpat_stage_anatomy"],
xpat_fish = config["ZFIN_url"]["xpat_fish"],
anatomy_synonyms = config["ZFIN_url"]["anatomy_synonyms"]
output:
anatomy_item = os.path.join(os.getcwd(), config["download_data_from_ZFIN"]["dir"], "anatomy_item.tsv"),
xpat_stage_anatomy = os.path.join(os.getcwd(), config["download_data_from_ZFIN"]["dir"], "xpat_stage_anatomy.tsv"),
xpat_fish = os.path.join(os.getcwd(), config["download_data_from_ZFIN"]["dir"], "xpat_fish.tsv"),
anatomy_synonyms = os.path.join(os.getcwd(), config["download_data_from_ZFIN"]["dir"], "anatomy_synonyms.tsv")
shell:
"wget -O {output.anatomy_item} {input.anatomy_item};" \
"wget -O {output.anatomy_synonyms} {input.anatomy_synonyms};" \
"wget -O {output.xpat_stage_anatomy} {input.xpat_stage_anatomy};" \
"wget -O {output.xpat_fish} {input.xpat_fish};"
And this is the content of my configs.yaml file:
ZFIN_url:
# Zebrafish Anatomy Term
anatomy_item: "https://zfin.org/downloads/file/anatomy_item.txt"
# Zebrafish Gene Expression by Stage and Anatomy Term
xpat_stage_anatomy: "https://zfin.org/downloads/file/xpat_stage_anatomy.txt"
# ZFIN Genes with Expression Assay Records
xpat_fish: "https://zfin.org/downloads/file/xpat_fish.txt"
# Zebrafish Anatomy Term Synonyms
anatomy_synonyms: "https://zfin.org/downloads/file/anatomy_synonyms.txt"
download_data_from_ZFIN:
dir: ZFIN_data
The error message is:
Building DAG of jobs...
MissingInputException in line 10 of /home/zhangdong/works/NGS/coevolution/snakemake/coevolution.rule:
Missing input files for rule download_data_from_ZFIN:
https://zfin.org/downloads/file/anatomy_item.txt
I want to make sure that if this exception is caused by none file input for the input rule?
Note that you can also use remote files as input so you may avoid rule download_data_from_ZFIN altogether. E.g.:
from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider
HTTP = HTTPRemoteProvider()
rule all:
input:
'output.txt',
rule one:
input:
# Some file from the web
x= HTTP.remote('https://plasmodb.org/common/downloads/release-49/PbergheiANKA/txt/PlasmoDB-49_PbergheiANKA_CodonUsage.txt', keep_local=True)
output:
'output.txt',
shell:
r"""
# Do something with the remote file
head {input.x} > {output}
"""
The remote file will be downloaded and stored locally under plasmodb.org/common/.../PlasmoDB-49_PbergheiANKA_CodonUsage.txt
Many thanks #dariober, I tried the follwing code and it worked,
import os
from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider
configfile: "Configs.yaml"
HTTP = HTTPRemoteProvider()
rule all:
input:
expand(os.path.join(os.getcwd(),config["download_data_from_ZFIN"]["dir"],"{item}.tsv"),
item=list(config["ZFIN_url"].keys()))
rule download_data_from_ZFIN:
input:
lambda wildcards: HTTP.remote(config["ZFIN_url"][wildcards.item], keep_local=True)
output:
os.path.join(os.getcwd(),config["download_data_from_ZFIN"]["dir"],"{item}.tsv")
threads:
1
shell:
"mv {input} > {output}"
Such code is more snakemake-like, but I have two further questions:
Is there a way to specify the output file name for the downloading? Now I use the mv command to achieve that.
Does this remote files function support parallel works? I tried the above code together with --cores 6, but it still download the file one by one.
Related
A few days ago I started using Snakemake for the first time. I am having an issue when I am trying to run the megahit rule in my pipeline.
It gives me the following error "Outputs of incorrect type (directories when expecting files or vice versa). Output directories must be flagged with directory(). ......"
So initially it runs and then crashes with the above error. I implemented the solution with the directory() option in my pipeline but I think its not a good practice since, for various reasons, you can loose files without even knowing it.
Is there a way to run the rule without using the directory() ?
I would appreciate any help on the issue!
Thanking you in advance
sra = []
with open("run_ids") as f:
for line in f:
sra.append(line.strip())
rule all:
input:
expand("raw_reads/{sample}/{sample}.fastq", sample=sra),
expand("trimmo/{sample}/{sample}.trimmed.fastq", sample=sra),
expand("megahit/{sample}/final.contigs.fa", sample=sra)
rule download:
output:
"raw_reads/{sample}/{sample}.fastq"
params:
"--split-spot --skip-technical"
log:
"logs/fasterq-dump/{sample}.log"
benchmark:
"benchmarks/fastqdump/{sample}.fasterq-dump.benchmark.txt"
threads: 8
shell:
"""
fasterq-dump {params} --outdir /home/raw_reads/{wildcards.sample} {wildcards.sample} -e {threads}
"""
rule trim:
input:
"raw_reads/{sample}/{sample}.fastq"
output:
"trimmo/{sample}/{sample}.trimmed.fastq"
params:
"HEADCROP:15 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36"
log:
"logs/trimmo/{sample}.log"
benchmark:
"benchmarks/trimmo/{sample}.trimmo.benchmark.txt"
threads: 6
shell:
"""
trimmomatic SE -phred33 -threads {threads} {input} trimmo/{wildcards.sample}/{wildcards.sample}.trimmed.fastq {params}
"""
rule megahit:
input:
"trimmo/{sample}/{sample}.trimmed.fastq"
output:
"megahit/{sample}/final.contigs.fa"
params:
"-m 0.7 -t"
log:
"logs/megahit/{sample}.log"
benchmark:
"benchmarks/megahit/{sample}.megahit.benchmark.txt"
threads: 10
shell:
"""
megahit -r {input} -o {output} -t {threads}
"""
IMHO it is a bad design of the megahit software that it takes a directory as a parameter and outputs into a file in this directory with a hardcoded name. Flagging the filename with directory() doesn't solve the issue, as in this case what you expect to be a file with the .fa extension megahit treats as a directory. The rest of the pipeline is broken in this case.
But this issue can be solved in Snakemake like that:
rule megahit:
input:
"trimmo/{sample}/{sample}.trimmed.fastq"
output:
"megahit/{sample}/final.contigs.fa"
# ...
shell:
"""
megahit -r {input} -o megahit/{wildcards.sample} -t {threads}
"""
A better design of the megahit rule would look as follows:
rule megahit:
input:
"trimmo/{sample}/{sample}.trimmed.fastq"
output:
out_dir = directory("megahit/{sample}/"),
fasta = "megahit/{sample}/final.contigs.fa"
log:
"logs/megahit/{sample}.log"
benchmark:
"benchmarks/megahit/{sample}.megahit.benchmark.txt"
threads:
10
shell:
"megahit -r {input} -f -o {output.out_dir} -t {threads}"
This guarantees that the output directory is removed upon failure, while the -f argument to megahit tells it to ignore the fact that the output folder exists (it is created by Snakemake automatically because one of the outputs is a file inside it: final.contigs.fa).
BTW, the -m (--memory) parameter is best implemented as a resource. The only problem though is that snakemake's default resource, mem_mb is in megabytes. One workaround would be as follows:
resources:
mem_mb = mem_mb_limit_for_megahit # could be a fraction of a global constant
params:
mem_bytes = lambda w, resources: round(resources.mem_mb * 1e6)
shell:
"megahit ... -m {params.mem_bytes}"
Is there a way to write a rule so that I don't need to use the wildcards for all inputs/outputs or can I use a "*" to glob rather than using wildcards?? I want to symlink a file that is autocreated in subfolders, to the main directory.
This is the error I get when trying to run the Snakemake:
WildcardError in line 42 of snakemake_guppy_basecall/Snakefile:
Wildcards in input files cannot be determined from output files:
'failpass'
import glob
configfile: "config.yaml"
inputdirectory=config["directory"]
SAMPLES, = glob_wildcards(inputdirectory+"/{sample}.fast5", followlinks=True)
print(SAMPLES)
wildcard_constraints:
sample="\w+\d+_\w+_\w+\d+_.+_\d"
##### target rules #####
rule all:
input:
#expand('basecall/{sample}/sequencing_summary.txt', sample=SAMPLES),
"qc/multiqc.html"
rule make_indvidual_samplefiles:
input:
inputdirectory+"/{sample}.fast5",
output:
"lists/{sample}.txt",
shell:
"basename {input} > {output}"
rule guppy_basecall_persample:
input:
directory=directory(inputdirectory),
samplelist="lists/{sample}.txt",
output:
summary="basecall/{sample}/sequencing_summary.txt",
directory=directory("basecall/{sample}/"),
params:
config["basealgo"]
shell:
"guppy_basecaller -i {input.directory} --input_file_list {input.samplelist} -s {output.directory} -c {params} --compress_fastq -x \"auto\" --gpu_runners_per_device 3 --num_callers 2 --chunks_per_runner 200"
rule guppy_linkfastq:
input:
#glob_wildcards("basecall/{sample}/*/*.fastq.gz"),
"basecall/{sample}/{failpass}/{runid}.fastq.gz",
output:
"basecall/{sample}.fastq.gz",
shell:
"ln -s {input} {output}"
rule fastqc_pretrim:
input:
#"basecall/{sample}/{failpass}/{runid}.fastq.gz",
"basecall/{sample}.fastq.gz"
output:
html="qc/fastqc_pretrim/{sample}.html",
zip="qc/fastqc_pretrim/{sample}_fastqc.zip" # the suffix _fastqc.zip is necessary for multiqc to find the file. If not using multiqc, you are free to choose an arbitrary filename
params: ""
log:
"logs/fastqc_pretrim/{sample}.log"
threads: 1
wrapper:
"v0.75.0/bio/fastqc"
rule multiqc:
input:
#expand("basecall/{sample}.fastq.gz", sample=SAMPLES)
expand("qc/fastqc_pretrim/{sample}_fastqc.zip", sample=SAMPLES)
output:
"qc/multiqc.html"
params:
"" # Optional: extra parameters for multiqc.
log:
"logs/multiqc.log"
wrapper:
"0.77.0/bio/multiqc"
I am trying to create a pipeline that does: Get Nanopore f5 sequence files -> run guppy basecaller GPU mode -> use resulting fastq files to run FASTQC -> run multiQC for everything
I am writing a snakemake to produce Sars-Cov-2 variants from Nanopore sequencing. The pipeline that I am writing is based on the artic network, so I am using artic guppyplex and artic minion.
The snakemake that I wrote has the following steps:
zip all the fastq files for all barcodes (rule zipFq)
perform read filtering with guppyplex (rule guppyplex)
call the artic minion pipeline (rule minion)
move the stderr and stdout from qsub to a folder under the working directory (rule mvQsubLogs)
Below is the snakemake that I wrote so far, which works
barcodes = ['barcode49', 'barcode50', 'barcode51']
rule all:
input:
expand([
# zip fq
"zipFastq/{barcode}/{barcode}.zip",
# guppyplex
"guppyplex/{barcode}/{barcode}.fastq",
# nanopolish
"nanopolish/{barcode}",
# directory where the logs will be moved to
"logs/{barcode}"
], barcode = barcodes)
rule zipFq:
input:
FQ = f"{FASTQ_PATH}/{{barcode}}"
output:
"zipFastq/{barcode}/{barcode}.zip"
shell:
"zip {output} {input.FQ}/*"
rule guppyplex:
input:
FQ = f"{FASTQ_PATH}/{{barcode}}" # FASTQ_PATH is parsed from config.yaml
output:
"guppyplex/{barcode}/{barcode}.fastq"
shell:
"/home/ngs/miniconda3/envs/artic-ncov2019/bin/artic guppyplex --skip-quality-check --min-length {MINLENGTHGUPPY} --max-length {MAXLENGTHGUPPY} --directory {input.FQ} --prefix {wildcards.barcode} --output {output}" # variables in CAPITALS are parsed from config.yaml
rule minion:
input:
INFQ = rules.guppyplex.output,
FAST5 = f"{FAST5_PATH}/{{barcode}}"
params:
OUTDIR = "nanopolish/{barcode}"
output:
directory("nanopolish/{barcode}")
shell:
"""
mkdir {params.OUTDIR};
cd {params.OUTDIR};
export PATH=/home/ngs/miniconda3/envs/artic-ncov2019/bin:$PATH;
artic minion --normalise {NANOPOLISH_NORMALISE} --threads {THREADS} --scheme-directory {PRIMERSDIR} --read-file ../../{input.INFQ} --sequencing-summary {Seq_Sum} --fast5-directory {input.FAST5} nCoV-2019/{PRIMERVERSION} {wildcards.barcode} # variables in CAPITALS are parsed from config.yaml
"""
rule mvQsubLogs:
input:
# zipFQ
rules.zipFq.output,
# guppyplex
rules.guppyplex.output,
# nanopolish
rules.minion.output
output:
directory("logs/{barcode}")
shell:
"mkdir -p {output} \n"
"mv {LOGDIR}/{wildcards.barcode}* {output}/"
The above snakemake works and now I am trying to add another rule, but the difference here is that this rule is an aggregate function i.e. it should not be called for every barcode, but only once after all the rules are called for all barcodes
The rule that I am trying to incorporate (catFasta) would cat all {barcode}.consensus.fasta (generated by rule minion) into in a single file, as shown below (incorporated into the snakemake above):
barcodes = ['barcode49', 'barcode50', 'barcode51']
rule all:
input:
expand([
# zip fq
"zipFastq/{barcode}/{barcode}.zip",
# guppyplex
"guppyplex/{barcode}/{barcode}.fastq",
# nanopolish
"nanopolish/{barcode}",
# catFasta
"catFasta/cat_consensus.fasta",
# directory where the logs will be moved to
"logs/{barcode}"
], barcode = barcodes)
rule zipFq:
input:
FQ = f"{FASTQ_PATH}/{{barcode}}"
output:
"zipFastq/{barcode}/{barcode}.zip"
shell:
"zip {output} {input.FQ}/*"
rule guppyplex:
input:
FQ = f"{FASTQ_PATH}/{{barcode}}" # FASTQ_PATH is parsed from config.yaml
output:
"guppyplex/{barcode}/{barcode}.fastq"
shell:
"/home/ngs/miniconda3/envs/artic-ncov2019/bin/artic guppyplex --skip-quality-check --min-length {MINLENGTHGUPPY} --max-length {MAXLENGTHGUPPY} --directory {input.FQ} --prefix {wildcards.barcode} --output {output}" # variables in CAPITALS are parsed from config.yaml
rule minion:
input:
INFQ = rules.guppyplex.output,
FAST5 = f"{FAST5_PATH}/{{barcode}}"
params:
OUTDIR = "nanopolish/{barcode}"
output:
directory("nanopolish/{barcode}")
shell:
"""
mkdir {params.OUTDIR};
cd {params.OUTDIR};
export PATH=/home/ngs/miniconda3/envs/artic-ncov2019/bin:$PATH;
artic minion --normalise {NANOPOLISH_NORMALISE} --threads {THREADS} --scheme-directory {PRIMERSDIR} --read-file ../../{input.INFQ} --sequencing-summary {Seq_Sum} --fast5-directory {input.FAST5} nCoV-2019/{PRIMERVERSION} {wildcards.barcode} # variables in CAPITALS are parsed from config.yaml
"""
rule catFasta:
input:
expand("nanopolish/{barcode}/{barcode}.consensus.fasta", barcode = barcodes)
output:
"catFasta/cat_consensus.fasta"
shell:
"cat {input} > {output}"
rule mvQsubLogs:
input:
# zipFQ
rules.zipFq.output,
# guppyplex
rules.guppyplex.output,
# nanopolish
rules.minion.output,
# catFasta
rules.catFasta.output
output:
directory("logs/{barcode}")
shell:
"mkdir -p {output} \n"
"mv {LOGDIR}/{wildcards.barcode}* {output}/"
However, when I call snakemake with
(artic-ncov2019) ngs#bngs05b:/nexusb/SC2/ONT/scripts/SnakeMake> snakemake -np -s Snakefile_v2 --cluster "qsub -q onlybngs05b -e {LOGDIR} -o {LOGDIR} -j y" -j 5 --jobname "{wildcards.barcode}.{rule}.{jobid}" all # LOGDIR parsed from config.yaml
I get:
Building DAG of jobs...
MissingInputException in line 178 of /nexusb/SC2/ONT/scripts/SnakeMake/Snakefile_v2:
Missing input files for rule guppyplex:
/nexus/Gridion/20210521_Covid7/Covid7/20210521_0926_X1_FAL11796_a5b62ac2/fastq_pass/barcode49/barcode49.consensus.fasta
Which I don't find easy to understand: snakemake is complaining about /nexus/Gridion/20210521_Covid7/Covid7/20210521_0926_X1_FAL11796_a5b62ac2/fastq_pass/barcode49/barcode49.consensus.fasta whereas /nexus/Gridion/20210521_Covid7/Covid7/20210521_0926_X1_FAL11796_a5b62ac2/fastq_pass/ is FASTQ_PATH and I am not defining f"{FASTQ_PATH}/{{barcode}}.consensus.fasta" anywhere
A very same problem is described here, though the strategy in the accepted answer (the input for rule catFasta would be expand("nanopolish/{{barcode}}/{{barcode}}.consensus.fasta")) does not work for me.
Does anyone know how I can circumvent this?
The rule that fails is rule guppyplex, which looks for an input in the form of {FASTQ_PATH}/{{barcode}}.
Looks like the wildcard {barcode} is filled with barcode49/barcode49.consensus.fasta, which happened because of two reasons I think:
First (and most important): The workflow does not find a better way to produce the final output. In rule catFasta, you give an input file which is never described as an output in your workflow. The rule minion has the directory as an output, but not the file, and it is not perfectly clear for the workflow where to produce this input file.
It therefore infers that the {barcode} wildcard somehow has to contain this .consensus.fasta that it has never seen before. This wildcard is then handed over to the top, where the workflow crashes since it cannot find a matching input file.
Second: This initialisation of the wildcard with sth. you don't want is only possible since you did not constrain the wildcard properly. You can for example forbid the wildcard to contain a . (see wildcard_constraints here)
However, the main problem is that catFasta does not find the desired input. I'd suggest changing the output of minion to "nanopolish/{barcode}/{barcode}.consensus.fasta", since the you already take the OUTDIR from the params, that should not hurt your rule here.
Edit: Dummy test example:
barcodes = ['barcode49', 'barcode50', 'barcode51']
rule all:
input:
expand([
# guppyplex
"guppyplex/{barcode}/{barcode}.fastq",
# catFasta
"catFasta/cat_consensus.fasta",
], barcode = barcodes)
rule guppyplex:
input:
FQ = f"fastq/{{barcode}}" # FASTQ_PATH is parsed from config.yaml
output:
"guppyplex/{barcode}/{barcode}.fastq"
shell:
"touch {output}" # variables in CAPITALS are parsed from config.yaml
rule minion:
input:
INFQ = rules.guppyplex.output,
FAST5 = f"fasta/{{barcode}}"
params:
OUTDIR = "nanopolish/{barcode}"
output:
"nanopolish/{barcode}/{barcode}.consensus.fasta"
shell:
"""
touch {output} && echo {wildcards.barcode} > {output}
"""
rule catFasta:
input:
expand("nanopolish/{barcode}/{barcode}.consensus.fasta", barcode = barcodes)
output:
"catFasta/cat_consensus.fasta"
shell:
"cat {input} > {output}"
My problem is related to Running parallel instances of a single job/rule on Snakemake but I believe different.
I cannot create a all: rule for it in advance because the folder of input files will be created by a previous rule and depends on the user initial data
pseudocode
rule1: get a big file (OK)
rule2: split the file in parts in Split folder (OK)
rule3: run a program on each file created in Split
I am now at rule3 with Split containing 70 files like
Split/file_001.fq
Split/file_002.fq
..
Split/file_069.fq
Could you please help me creating a rule for pigz to run compress the 70 files in parallel to 70 .gz files
I am running with snakemake -j 24 ZipSplit
config["pigt"] gives 4 threads for each compression job and I give 24 threads to snakemake so I expect 6 parallel compressions but my current rule merges the inputs to one archive in a single job instead of parallelizing !?
Should I build the list of input fully in the rule? how?
# parallel job
files, = glob_wildcards("Split/{x}.fq")
rule ZipSplit:
input: expand("Split/{x}.fq", x=files)
threads: config["pigt"]
shell:
"""
pigz -k -p {threads} {input}
"""
I tried to define input directly with
input: glob_wildcards("Split/{x}.fq")
but syntax error occures
# InSilico_PCR Snakefile
import os
import re
from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider
HTTP = HTTPRemoteProvider()
# source config variables
configfile: "config.yaml"
# single job
rule GetRawData:
input:
HTTP.remote(os.path.join(config["host"], config["infile"]), keep_local=True, allow_redirects=True)
output:
os.path.join("RawData", config["infile"])
run:
shell("cp {input} {output}")
# single job
rule SplitFastq:
input:
os.path.join("RawData", config["infile"])
params:
lines_per_file = config["lines_per_file"]
output:
pfx = os.path.join("Split", config["infile"] + "_")
shell:
"""
zcat {input} | split --numeric-suffixes --additional-suffix=.fq -a 3 -l {params.lines_per_file} - {output.pfx}
"""
# parallel job
files, = glob_wildcards("Split/{x}.fq")
rule ZipSplit:
input: expand("Split/{x}.fq", x=files)
threads: config["pigt"]
shell:
"""
pigz -k -p {threads} {input}
"""
I think the example below should do it, using checkpoints as suggested by #Maarten-vd-Sande.
However, in your particular case of splitting a big file and compress the output on the fly, you may be better off using the --filter option of split as in
split -a 3 -d -l 4 --filter='gzip -c > $FILE.fastq.gz' bigfile.fastq split/
The snakemake solution, assuming your input file is called bigfile.fastq, split and compress output will be in directory splitting./bigfile/
rule all:
input:
expand("{sample}.split.done", sample= ['bigfile']),
checkpoint splitting:
input:
"{sample}.fastq"
output:
directory("splitting/{sample}")
shell:
r"""
mkdir splitting/{wildcards.sample}
split -a 3 -d --additional-suffix .fastq -l 4 {input} splitting/{wildcards.sample}/
"""
rule compress:
input:
"splitting/{sample}/{i}.fastq",
output:
"splitting/{sample}/{i}.fastq.gz",
shell:
r"""
gzip -c {input} > {output}
"""
def aggregate_input(wildcards):
checkpoint_output = checkpoints.splitting.get(**wildcards).output[0]
return expand("splitting/{sample}/{i}.fastq.gz",
sample=wildcards.sample,
i=glob_wildcards(os.path.join(checkpoint_output, "{i}.fastq")).i)
rule all_done:
input:
aggregate_input
output:
touch("{sample}.split.done")
I want to write a pipeline in snakemake that takes an input file from config.yaml, runs a command, and writes the output to the current directory under the original filename + new suffix.
Snakefile
configfile: "config.yaml"
rule target:
input:
config["reads"]+".fasta.gz",
rule raw_convert:
input:
config["reads"]
output:
config["reads"]+".fasta.gz" # old path specified here
shell:
"sed -n '1~4s/^#/>/p;2~4p' {input} | gzip > {output}"
config.yaml
reads: /path/to/dir/myreads.fq.gz
Using bash, I would write something like to get the file myreads.fq.gz.fasta.gz:
sed -n '1~4s/^#/>/p;2~4p' ${input} | gzip >$(basename ${input}).fasta.gz
In this solution, I pair read basenames to their full path in a dict, and then use it in rules. This would fail if basenames are not unique though.
import os
d = {}
for read in config["reads"]:
basename = os.path.basename(read)
d[basename] = read
rule all:
input:
expand('{read_basename}.fasta.gz', read_basename=list(d.keys()))
rule xxx:
input:
lambda wildcards: d[wildcards.read_basename]
output:
"{read_basename}.fasta.gz"
shell:
'soemthing'
You may want to replace .fq.gz with .fasta.gz instead of appending them. For readability purposes.
I finally came up with some code that seems to do the trick:
configfile: "config.yaml"
import os
basenamereads = os.path.basename(config["reads"])
rule target:
input: expand("{myoutput}.fasta.gz", myoutput=basenamereads)
rule xxx:
input:
config["reads"]
output:
os.path.basename(config["reads"])+".fasta.gz"
shell:
"cat {input} >{output}"