mapping reads using snakemake - yaml

Question

I am trying to run hisat2 mapping using the snakemake.
Basically, I'm using a config.yaml file like this:
reads:
set1: /path/to/set1/samplelist.tab
hisat2:
database: genome
genome: genome.fa
nodes: 2
memory: 8G
arguments: --dta
executables:
hisat2: /Tools/hisat2-2.1.0/hisat2
samtools: /Tools/samtools-1.3/samtools
Then Snakefile:
configfile: "config.yaml"
workdir: "/path/to/working_dir/"
# Hisat2
rule hisat2:
input:
reads = lambda wildcards: config["reads"][wildcards.sample]
output:
bam = "{sample}/{sample}.bam"
params:
idx=config["hisat2"]["database"],
executable = config["executables"]["hisat2"],
nodes = config["hisat2"]["nodes"],
memory = config["hisat2"]["memory"],
executable2 = config["executables"]["samtools"]
run:
shell("{params.executable} --dta -p {params.nodes} -x {params.idx} {input.reads} |"
"{params.executable2} view -Sbh -o {output.bam} -")
# all
rule all:
input:
lambda wildcards: [sample + "/" + sample + ".bam"
for sample in config["reads"].keys()]
My samplelist.tab is like this:
id reads1 reads2
set1a set1a_R1.fastq.gz set1a_R2.fastq.gz
set1b set1b_R1.fastq.gz set1b_R2.fastq.gz
Any hints how to make this working? I apoligize for a messy script, just started using snakemake.

Answer 1

You will have to do something like this:
import pandas as pd
reads = pd.read_csv(config["reads"]['set1'], sep='\t', index_col=0)
def get_fastq(wildcards):
return list(reads.loc[wildcards.sample].values)
rule hisat2:
input:
get_fastq
...
First you will need to load the samplelist and store this (I did it as a pandas dataframe). Then you can lookup which files belong to that sample name.
Edit:
Rewriting the code to look like this is much more readable (in my opinion).
rule hisat2:
input:
[{sample}_R1.fastq.gz,
{sample}_R2.fastq.gz]
...