How to handle ftp links provided in config file in snakemake? - python

I am attempting to build a snakemake workflow that will provide a symlink to a local file if it exists or if the file does not exist will download the file and integrate it into the workflow. To do this I am using two rules with the same output with preference given to the linking rule (ln_fastq_pe below) using ruleorder.
Whether the file exists or not is known before execution of the workflow. The file paths or ftp links are provided in tab-delimited config file that is used by the workflow to read in samples.
e.g. the contents of samples.txt:
id sample_name fq1 fq2
b test_paired resources/SRR1945436_1.fastq.gz resources/SRR1945436_2.fastq.gz
c test_paired2 ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR194/005/SRR1945435/SRR1945435_1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR194/005/SRR1945435/SRR1945435_2.fastq.gz
relevant code from the workflow here:
import pandas as pd
from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider
FTP = FTPRemoteProvider()
configfile: "config/config.yaml"
samples = pd.read_table("config/samples.tsv").set_index("id", drop=False)
all_ids=list(samples["id"])
ruleorder: ln_fastq_pe > dl_fastq_pe
rule dl_fastq_pe:
"""
download file from ftp link
"""
input:
fq1=lambda wildcards: FTP.remote(samples.loc[wildcards.id, "fq1"], keep_local=True),
fq2=lambda wildcards: FTP.remote(samples.loc[wildcards.id, "fq2"], keep_local=True)
output:
"resources/fq/{id}_1.fq.gz",
"resources/fq/{id}_2.fq.gz"
shell:
"""
mv {input.fq1} {output[0]}
mv {input.fq2} {output[1]}
"""
rule ln_fastq_pe:
"""
link file
"""
input:
fq1=lambda wildcards: samples.loc[wildcards.id, "fq1"],
fq2=lambda wildcards: samples.loc[wildcards.id, "fq2"]
output:
"resources/fq/{id}_1.fq.gz",
"resources/fq/{id}_2.fq.gz"
shell:
"""
ln -sr {input.fq1} {output[0]}
ln -sr {input.fq2} {output[1]}
"""
When I run this workflow, I receive the following error pointing to the line describing the ln_fastq_pe rule.
WorkflowError in line 58 of /path/to/Snakefile:
Function did not return str or list of str.
I think the error is in how I am describing the FTP links in the samples.txt config file in the dl_fastq_pe rule. What is the proper way to describe FTP links given in a tabular config file so that snakemake will understand them and can download and use the files in a workflow?
Also, is it possible to do what I am trying to do and will this method get me there? I have tried other solutions (e.g. using python code to check if file exists and executing one set of shell commands if it does and the other if it doesn't) to no avail.

You are trying to pass the objects from pandas to Snakemake. The latter expects the values of types str or list[str] in the input section of the rule, but the values you provide (samples.loc[wildcards.id, "fq1"]) are of type pandas.core.frame.DataFrame or pandas.core.series.Series. You need to convert them to what Snamemake expects. For example, this may help: samples.loc[wildcards.id, "fq1"].tolist().

I figured out how to do this by omitting input and instead reading in the fields from samples.tsv through params and merging the two rules into one rule. Snakemake is not picky about what is read in through params unlike input. I then use test command to ask if a file exists. If it exists, proceed with the symlink, if not, download with wget.
Solution is as follows:
import os
import pandas as pd
samples = pd.read_table("config/samples.tsv").set_index("id", drop=False)
all_ids=list(samples["id"])
rule all:
input:
expand("resources/fq/{id}_1.fq.gz", id=all_ids),
expand("resources/fq/{id}_2.fq.gz", id=all_ids)
rule dl_fastq_pe:
"""
if file exists, symlink. If file doesn't exist, download to resources
"""
params:
fq1=lambda wildcards: samples.loc[wildcards.id,"fq1"],
fq2=lambda wildcards: samples.loc[wildcards.id,"fq2"]
output:
"resources/fq/{id}_1.fq.gz",
"resources/fq/{id}_2.fq.gz"
shell:
"""
if test -f {params.fq1}
then
ln -sr {params.fq1} {output[0]}
ln -sr {params.fq2} {output[1]}
else
wget --no-check-certificate -O {output[0]} {params.fq1}
wget --no-check-certificate -O {output[1]} {params.fq2}
fi
"""

Related

Snakemake pipeline using directories and files

I am building a snakemake pipeline with python scripts.
Some of the python scripts take as input a directory, while others take as input files inside those directories.
I would like to be able to do have some rules which take as input the directory and some that take as input the files. Is this possible?
Example of what I am doing showing only two rules:
FILES = glob.glob("data/*/*raw.csv")
FOLDERS = glob.glob("data/*/")
rule targets:
input:
processed_csv = expand("{files}raw_processed.csv", files =FILES),
normalised_csv = expand("{folders}/normalised.csv", folders=FOLDERS)
rule process_raw_csv:
input:
script = "process.py",
csv = "{sample}raw.csv"
output:
processed_csv = "{sample}raw_processed.csv"
shell:
"python {input.script} -i {input.csv} -o {output.processed_csv}"
rule normalise_processed_csv:
input:
script = "normalise.py",
processed_csv = "{sample}raw_processed.csv" #This is input to the script but is not parsed, instead it is fetched within the code normalise.py
params:
folder = "{folders}"
output:
normalised_csv = "{folders}/normalised.csv" # The output
shell:
"python {input.script} -i {params.folder}"
Some python scripts (process.py) take all the files they needed or produced as inputs and they need to be parsed. Some python scripts only take the main directory as input and the inputs are fetched inside and the outputs are written on it.
I am considering rewriting all the python scripts so that they take the main directory as input, but I think there could be a smart solution to be able to run these two types on the same snakemake pipeline.
Thank you very much in advance.
P.S. I have checked and this question is similar but not the same: Process multiple directories and all files within using snakemake
I would like to be able to do have some rules which take as input the directory and some that take as input the files. Is this possible?
I don't see anything special with this requirement... What about this?
rule one:
output:
d=directory('{sample}'),
a='{sample}/a.txt',
b='{sample}/b.txt',
shell:
r"""
mkdir -p {output.d}
touch {output.a}
touch {output.b}
"""
rule use_dir:
input:
d='{sample}',
output:
out='outdir/{sample}.out',
shell:
r"""
cat {input.d}/* > {output.out}
"""
rule use_files:
input:
a='{sample}/a.txt',
b='{sample}/b.txt',
output:
out='outfiles/{sample}.out',
shell:
r"""
cat {input.a} {input.b} > {output.out}
"""
rule use_dir will use the content of directory {sample}, whatever it contains. Rule use_files will use specifically files a.txt and b.txt from directory {sample}.

Running multiple config files with Bppancestor

I need to run Bppancestor with multiple config files, I have tried different approaches but none of them worked. I have around 150 files, so doing it one by one is not an efficient solution.
The syntax to run bppancestor is the following one:
bppancestor params=config_file
I tried doing:
bppancestor params=directory_of_config_files/*
and using a Snakefile to try to automatize the workflow:
ARCHIVE_FILE = 'bpp_output.tar.gz'
# a single config file
CONFIG_FILE = 'config_files/{sims}.conf'
# Build the list of input files.
CONF = glob_wildcards(CONFIG_FILE).sims
# pseudo-rule that tries to build everything.
# Just add all the final outputs that you want built.
rule all:
input: ARCHIVE_FILE
# run bppancestor
rule bpp:
input:
CONF,
shell:
'bppancestor params={input}'
# create an archive with all results
rule create_archive:
input: CONF,
output: ARCHIVE_FILE
shell: 'tar -czvf {output} {input}'
Could someone give me advice on this?
You're very close. Rule bpp should use as input a specific config file and specify concrete output (not sure if the output is a file or a folder). If I understand the syntax correctly, this link suggests that output files can be specified using output.sites.file and output.nodes.file:
rule bpp:
input:
CONFIG_FILE,
output:
sites='sites.{sims}',
nodes='nodes.{sims}',
shell:
'bppancestor params={input} output.sites.file={output.sites} output.nodes.file={output.nodes}'
Rule create_archive will collect all the outputs and archive them:
rule create_archive:
input: expand('sites.{sims}', CONF), expand('nodes.{sims}', CONF)
output: ARCHIVE_FILE
shell: 'tar -czvf {output} {input}'

snakemake - wildcards from python dictionary

I am writing a snakemake file that has input files on a specific location, with specific folder names (for this example, barcode9[456]). I need to change the naming conventions in these directories so I now want to add a first rule to my snakemake, which would link the folders in the original location (FASTQ_PATH) to an output folder in the snakemake working directory. The names of the link folders in this directory come from a python dictionay d, defined in the snakemake. I would then use these directories as input for the downstream rules.
So the first rule of my snakemake is actually a python script (scripts/ln.py) that maps the naming convention in the original directory to the desired naming conventions, and links the fastqs:
The snakemake looks like so:
FASTQ_PATH = '/path/to/original_location'
# dictionary that maps the subdirectories in FASTQ_PATH (keys) with the directory names that I want in the snakemake working directory (values)
d = {'barcode94': 'IBC_UZL-CV5-04',
'barcode95': 'IBC_UZL-CV5-42',
'barcode96': 'IBC_UZL-CV5-100'}
rule all:
input:
expand('symLinkFq/{barcode}', barcode = list(d.values())) # for each element in list(d.values()) I want to create a subdirectory that would point to the corresponding path in the original location (FASTQ_PATH)
rule symlink:
input:
FASTQ_PATH,
d
output:
'symLinkFq/{barcode}'
script:
"scripts/ln.py"
The python script that I am calling to make the links is shown below
import pandas as pd
import subprocess as sp
import os
# parsing variables from Snakefile
d_sampleNames = snakemake.input[1]
fastq_path = snakemake.input[0]
os.makedirs('symLinkFq')
for barcode in list(d_sampleNames.keys()):
idx = list(d_sampleNames.keys()).index(barcode)
sampleName = list(d_sampleNames.values())[idx]
sp.run(f"ln -s {fastq_path}/{barcode} symLinkFq/{sampleName}", shell=True) # the relative path with respect to the working directory should suffice for the DEST in the ln -s command
But when I call snakemake -np -s Snakefile I get
Building DAG of jobs...
MissingInputException in line 15 of /nexusb/SC2/ONT/scripts/SnakeMake/minimalExample/renameFq/Snakefile:
Missing input files for rule symlink:
barcode95
barcode94
barcode96
The error kind of makes sense to me. The only 'input' files that I have are python variables instead of being files that do exist in my system.
I guess the issue that I am having comes down to the fact that the wildcards that I want to use for all rules are not present in any file that can be used as input, so what I can think of using is the dictionary with the correspondence, though it is not working as I tried.
Does anyone know how to get around this, any other different approach is welcome.
If I understand correctly, I think it could be easier...
I would reverse the key/value mapping (here with dict(zip(...))) than use a lambda input function to get the source directory for each output key:
FASTQ_PATH = '/path/to/files'
d = {'barcode94': 'IBC_UZL-CV5-04',
'barcode95': 'IBC_UZL-CV5-42',
'barcode96': 'IBC_UZL-CV5-100'}
d = dict(zip(d.values(), d.keys())) # Values become keys and viceversa
rule all:
input:
expand('symLinkFq/{barcode}', barcode = d.keys())
rule symlink:
input:
indir= lambda wc: os.path.join(FASTQ_PATH, d[wc.barcode]),
output:
outdir= directory('symLinkFq/{barcode}'),
shell:
r"""
ln -s {input.indir} {output.outdir}
"""
As an aside, in a python script I would use os.symlink() instead of spawning a subprocess and call ln -s - I think it's easier to debug if something goes wrong.

Snakemake - Rule that downloads data using sftp

I want to download files from a password protected FTP server in a Snakemake rule. I have seen the answer of Maarten-vd-Sande on specifying it using wildcards. Is it also possible using inputs without running into the MissingInputException?
FILES = ['file1.txt',
'file2.txt']
#remote file retrieval
rule download_file:
# replacing input by output would download all files in one job?
input:
file = expand("{file}", file=FILES)
shell:
# #this assumes your runtime has the SSHPASS env variable set
"sshpass -e sftp -B 258048 server<< get {input.file} data/{input.file}; exit"
I have seen the hint on the SFTP class in snakemake, but I am unsure how to use it in this context.
Thanks in advance!
I haven't tested this, but I am guessing something like this should work! We say that all the output we want is in rule all. Then we have the download rule to download those. I have no experience with using snakemake.remote, so I might be completely wrong in this though.
from snakemake.remote.SFTP import RemoteProvider
SFTP = RemoteProvider()
FILES = ['file1.txt',
'file2.txt']
rule all:
input:
FILES
rule download_file:
input:
SFTP.remote("{filename}.txt")
output:
"{filename}.txt"
# shell: # I am not sure if the shell keyword is required, if not, then you can remove these two lines.
# The : does nothing, just for the sake of having something there
# ":"
So I ended up using the following. The trick was how to pass the command to sftp using <<< "command". The envvars let snakemake check that the SSHPASSis set for sshpass to pick up.
envvars:
"SSHPASS"
#remote file retrieval
# #Idea: Replace using SFTP class
rule download_file:
output:
raw = temp(os.path.join(config['DATADIR'], "{file}", "{file}.txt"))
params:
file="{file}.txt"
resources:
walltime="300", nodes=1, mem_mb=2048
threads:
1
shell:
"sshpass -e sftp -B 258048 server <<< \"get {params.file} {output.raw} \""

Input Wildcard Constraints Snakemake

I am new to snakemake, and I am using it to merge steps from two pipelines into a single larger pipeline. The issue that several steps create similarly named files, and I cannot find a way to limit the wildcards, so I am getting a Missing input files for rule error on one step that I just cannot resolve.
The full snakefile is long, and is available here: https://mdd.li/snakefile
The relevant sections are (sections of the file are missing below):
wildcard_constraints:
sdir="[^/]+",
name="[^/]+",
prefix="[^/]+"
# Several mapping rules here
rule find_intersecting_snps:
input:
bam="hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.bam"
params:
hornet=os.path.expanduser(config['hornet']),
snps=config['snps']
output:
"hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.remap.fq1.gz",
"hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.remap.fq2.gz",
"hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.keep.bam",
"hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.to.remap.bam",
"hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.to.remap.num.gz"
shell:
dedent(
"""\
python2 {params.hornet}/find_intersecting_snps.py \
-p {input.bam} {params.snps}
"""
)
# Several remapping steps, similar to the first mapping steps, but in a different directory
rule wasp_merge:
input:
"hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.keep.bam",
"hic_mapping/wasp_results/{sdir}_{prefix}_filt_hg19.remap.kept.bam"
output:
"hic_mapping/wasp_results/{sdir}_{prefix}_filt_hg19.bwt2pairs.filt.bam"
params:
threads=config['job_cores']
shell:
dedent(
"""\
{module}
module load samtools
samtools merge --threads {params.threads} {output} {input}
"""
)
# All future steps use the name style wildcard, like below
rule move_results:
input:
"hic_mapping/wasp_results/{name}_filt_hg19.bwt2pairs.filt.bam"
output:
"hic_mapping/wasp_results/{name}_filt_hg19.bwt2pairs.bam"
shell:
dedent(
"""\
mv {input} {output}
"""
)
This pipeline is essentially doing some mapping steps in one directory structure that looks like hic_mapping/bowtie_results/bwt2/<subdir>/<file>, (where subdir is three different directories) then filtering the results, and doing another almost identical mapping step in hic_remap/bowtie_results/bwt2/<subdir>/<file>, before merging the results into an entirely new directory and collapsing the subdirectories into the file name: hic_mapping/wasp_results/<subdir>_<file>.
The problem I have is that the wasp_merge step breaks the find_intersecting_snps step if I collapse the subdirectory name into the filename. If I just maintain the subdirectory structure, everything works fine. Doing this would break future steps of the pipeline though.
The error I get is:
MissingInputException in line 243 of /godot/quertermous/PooledHiChip/pipeline/Snakefile:
Missing input files for rule find_intersecting_snps:
hic_mapping/bowtie_results/bwt2/HCASMC5-8_HCASMC-8-CAGAGAGG-TACTCCTT_S8_L006/001_hg19.bwt2pairs.bam
The correct file is:
hic_mapping/bowtie_results/bwt2/HCASMC5-8/HCASMC-8-CAGAGAGG-TACTCCTT_S8_L006_001_hg19.bwt2pairs.bam
But it is looking for:
hic_mapping/bowtie_results/bwt2/HCASMC5-8_HCASMC-8-CAGAGAGG-TACTCCTT_S8_L006/001_hg19.bwt2pairs.bam
Which is not created anywhere, nor defined by any rule. I think it is somehow getting confused by the existence of the file created by the wasp_merge step:
hic_mapping/wasp_results/HCASMC5-8_HCASMC-8-CAGAGAGG-TACTCCTT_S8_L006_001_filt_hg19.bwt2pairs.filt.bam
Or possibly a downstream file (after the target that creates this error):
hic_mapping/wasp_results/HCASMC5-8_HCASMC-8-CAGAGAGG-TACTCCTT_S8_L006_001_filt_hg19.bwt2pairs.bam
However, I have no idea why either of those files would confuse the find_intersecting_snps rule, because the directory structures are totally different.
I feel like I must be missing something obvious, because this error is so absurd, but I cannot figure out what it is.
The problem is that both the directory name and the file name contain underscores, and in the final file name I separate the two components by underscores.
By either changing that separation character, or replacing the rule with a python function that get the names from elsewhere, I can solve the issue.
This works:
rule wasp_merge:
input:
"hic_mapping/bowtie_results/bwt2/{sdir}/{prefix}_hg19.bwt2pairs.keep.bam",
"hic_mapping/wasp_results/{sdir}{prefix}_filt_hg19.remap.kept.bam"
output:
"hic_mapping/wasp_results/{sdir}{prefix}_filt_hg19.bwt2pairs.filt.bam"
params:
threads=config['job_cores']
shell:
dedent(
"""\
{module}
module load samtools
samtools merge --threads {params.threads} {output} {input}
"""
)

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