Using * to glob within an input file, or using multiple wildcards in input, then using only one wildcard for output? - snakemake

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

Related

snakemake - define input for aggregate rule without wildcards

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}"

snakemake running single jobs in parallel from all files in folder

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")

Snakemake: strip off path from input

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}"

snakemake - output one only file from multiple input files in one rule

I'm using snakemake for the first time in order to build a basic pipeline using cutadapt, bwa and GATK (trimming ; mapping ; calling). I would like to run this pipeline on every fastq file contained in a directory, without having to specify their name or whatever in the snakefile or in the config file. I would like to succeed in doing this.
The first two steps (cutadapt and bwa / trimming and mapping) are running fine, but I'm encountering some problems with GATK.
First, I have to generate g.vcf files from bam files. I'm doing this using these rules:
configfile: "config.yaml"
import os
import glob
rule all:
input:
"merge_calling.g.vcf"
rule cutadapt:
input:
read="data/Raw_reads/{sample}_R1_{run}.fastq.gz",
read2="data/Raw_reads/{sample}_R2_{run}.fastq.gz"
output:
R1=temp("trimmed_reads/{sample}_R1_{run}.fastq.gz"),
R2=temp("trimmed_reads/{sample}_R2_{run}.fastq.gz")
threads:
10
shell:
"cutadapt -q {config[Cutadapt][Quality_value]} -m {config[Cutadapt][min_length]} -a {config[Cutadapt][forward_adapter]} -A {config[Cutadapt][reverse_adapter]} -o {output.R1} -p '{output.R2}' {input.read} {input.read2}"
rule bwa_map:
input:
genome="data/genome.fasta",
read=expand("trimmed_reads/{{sample}}_{pair}_{{run}}.fastq.gz", pair=["R1", "R2"])
output:
temp("mapped_bam/{sample}_{run}.bam")
threads:
10
params:
rg="#RG\\tID:{sample}\\tPL:ILLUMINA\\tSM:{sample}"
shell:
"bwa mem -t 2 -R '{params.rg}' {input.genome} {input.read} | samtools view -Sb - > {output}"
rule picard_sort:
input:
"mapped_bam/{sample}.bam"
output:
"sorted_reads/{sample}.bam"
shell:
"java -Xmx4g -jar /home/alexandre/picard-tools/picard.jar SortSam I={input} O={output} SO=coordinate VALIDATION_STRINGENCY=SILENT"
rule picard_rmdup:
input:
bam="sorted_reads/{sample}.bam"
output:
"rmduped_reads/{sample}.bam",
"picard_stats/{sample}.bam"
params:
reads="rmduped_reads/{sample}.bam",
stats="picard_stats/{sample}.bam",
shell:
"java -jar -Xmx2g /home/alexandre/picard-tools/picard.jar MarkDuplicates "
"I={input.bam} "
"O='{params.reads}' "
"VALIDATION_STRINGENCY=SILENT "
"MAX_FILE_HANDLES_FOR_READ_ENDS_MAP=1000 "
"REMOVE_DUPLICATES=TRUE "
"M='{params.stats}'"
rule samtools_index:
input:
"rmduped_reads/{sample}.bam"
output:
"rmduped_reads/{sample}.bam.bai"
shell:
"samtools index {input}"
rule GATK_raw_calling:
input:
bam="rmduped_reads/{sample}.bam",
bai="rmduped_reads/{sample}.bam.bai",
genome="data/genome.fasta"
output:
"Raw_calling/{sample}.g.vcf",
shell:
"java -Xmx4g -jar /home/alexandre/GenomeAnalysisTK-3.7/GenomeAnalysisTK.jar -ploidy 2 --emitRefConfidence GVCF -T HaplotypeCaller -R {input.genome} -I {input.bam} --genotyping_mode DISCOVERY -o {output}"
These rules work fine. For example, if I have the files :
Cla001d_S281_L001_R1_001.fastq.gz
Cla001d_S281_L001_R2_001.fastq.gz
I can create one bam file (Cla001d_S281_L001_001.bam) and from that bam file create a GVCF file (Cla001d_S281_L001_001.g.vcf). I have a lot of sample like this one, and I need to create one GVCF file for each, and then merge these GVCF files into one file. The problem is that I'm unable to give the list of the file to merge to the following rule:
rule GATK_merge:
input:
???
output:
"merge_calling.g.vcf"
shell:
"java -Xmx4g -jar /home/alexandre/GenomeAnalysisTK-3.7/GenomeAnalysisTK.jar "
"-T CombineGVCFs "
"-R data/genome.fasta "
"--variant {input} "
"-o {output}"
I tried several things in order to do that, but cannot succeed. The problem is the link between the two rules (GATK_raw_calling and GATK_merge that is supposed to merge the output of GATK_raw_calling). I can't output one single file if I'm specifying the output of GATK_raw_calling as the input of the following rule (Wildcards in input files cannot be determined from output files), and I'm unable to make a link between the two rules if I'm not specifying these files as an input...
Is there a way to succeed in doing that? The difficulty is that I'm not defining a list of names or whatever, I think.
Thanks you in advance for your help.
You can try to generate a list of sample IDs using glob_wildcards on the initial fastq.gz files:
sample_ids, run_ids = glob_wildcards("data/Raw_reads/{sample}_R1_{run}.fastq.gz")
Then, you can use this to expand the input of GATK_merge:
rule GATK_merge:
input:
expand("Raw_calling/{sample}_{run}.g.vcf",
sample=sample_ids, run=run_ids)
If the same run ID always come with the same sample ID, you will need to zip instead of expanding, in order to avoid non-existing combinations:
rule GATK_merge:
input:
["Raw_calling/{sample}_{run}.g.vcf".format(
sample=sample_id,
run=run_id) for sample_id, run_id in zip(sample_ids, run_ids)]
You can achieve this by using a python function as an input for your rule, as described in the snakemake documentation here.
Could look like this for example:
# Define input files
def gatk_inputs(wildcards):
files = expand("Raw_calling/{sample}.g.vcf", sample=<samples list>)
return files
# Rule
rule gatk:
input: gatk_inputs
output: <output file name>
run: ...
Hope this helps.

Snakemake: remove output file

I don't see how to use a Snakemake rule to remove a Snakemake output file that has become useless.
In concrete terms, I have a rule bwa_mem_sam that creates a file named {sample}.sam.
I have this other rule, bwa_mem_bam that creates a file named {sample.bam}.
Has the two files contain the same information in different formats, I'd like to remove the first one cannot succeed doing this.
Any help would be very much appreciated.
Ben.
rule bwa_mem_map:
input:
sam="{sample}.sam",
bam="{sample}.bam"
shell:
"rm {input.sam}"
# Convert SAM to BAM.
rule bwa_mem_map_bam:
input:
rules.sam_to_bam.output
# Use bwa mem to map reads on a reference genome.
rule bwa_mem_map_sam:
input:
reference=reference_genome(),
index=reference_genome_index(),
fastq=lambda wildcards: config["units"][SAMPLE_TO_UNIT[wildcards.sample]],
output:
"mapping/{sample}.sam"
threads: 12
log:
"mapping/{sample}.log"
shell:
"{BWA} mem -t {threads} {input.reference} {input.fastq} > {output} 2> {log} "\
"|| (rc=$?; cat {log}; exit $rc;)"
rule sam_to_bam:
input:
"{prefix}.sam"
output:
"{prefix}.bam"
threads: 8
shell:
"{SAMTOOLS} view --threads {threads} -b {input} > {output}"
You don't need a rule to remove you sam files. Just mark the ouput sam file in "bwa_mem_map_sam" rule as temporary:
rule bwa_mem_map_sam:
input:
reference=reference_genome(),
index=reference_genome_index(),
fastq=lambda wildcards: config["units"][SAMPLE_TO_UNIT[wildcards.sample]],
output:
temp("mapping/{sample}.sam")
threads: 12
log:
"mapping/{sample}.log"
shell:
"{BWA} mem -t {threads} {input.reference} {input.fastq} > {output} 2> {log} "\
"|| (rc=$?; cat {log}; exit $rc;)"
as soon as a temp file is not needed anymore (ie: not used as input in any other rule), it will be removed by snakemake.
EDIT AFTER COMMENT:
If I understand correctly, your statement "if the user asks for a sam..." means the sam file is put in the target rule. If this is the case, then as long as the input of the target rule contains the sam file, the file won't be deleted (I guess). If the bam file is put in the target rule (and not the sam), then it will be deleted.
The other way is this:
rule bwa_mem_map:
input:
sam="{sample}.sam",
bam="{sample}.bam"
output:
touch("{sample}_samErased.txt")
shell:
"rm {input.sam}"
and ask for "{sample}_samErased.txt" in the target rule.
Based on the comments above, you want to ask the user if he wants a sam or bam output.
You could use this as a config argument:
snakemake --config output_format=sam
Then you use this kind Snakefile:
samples = ['A','B']
rule all:
input:
expand('{sample}.mapped.{output_format}', sample=samples, output_format=config['output_format'])
rule bwa:
input: '{sample}.fastq'
output: temp('{sample}.mapped.sam')
shell:
"""touch {output}"""
rule sam_to_bam:
input: '{sample}.mapped.sam'
output: '{sample}.mapped.bam'
shell:
"""touch {output}"""