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Snakefile
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397 lines (341 loc) · 12 KB
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# slide_snake
## Snakemake workflow to align and quantify spatial transriptomics datasets
import pandas as pd
import os
### Config #############################################################################
configfile: "config.yaml"
RECIPE_SHEET = pd.read_csv(config["RECIPE_SHEET"], na_filter=False, index_col=0)
### Directory locations ################################################################
TMPDIR = os.path.abspath(config["TMPDIR"])
OUTDIR = config["OUTDIR"]
# OUTDIR = os.path.abspath(config["OUTDIR"])
### Variables and references ###########################################################
SAMPLE_SHEET = pd.read_csv(config["SAMPLE_SHEET_PATH"], na_filter=False)
SAMPLE_SHEET.index = SAMPLE_SHEET["sampleID"]
SAMPLES = list(SAMPLE_SHEET["sampleID"])
# short-read data
R1_FQS = dict(zip(SAMPLES, list(SAMPLE_SHEET["fastq_R1"])))
R1_FQS = {SAMP: READ.split() for SAMP, READ in R1_FQS.items() if READ}
R2_FQS = dict(zip(SAMPLES, list(SAMPLE_SHEET["fastq_R2"])))
R2_FQS = {SAMP: READ.split() for SAMP, READ in R2_FQS.items() if READ}
# long-read data
ONT = dict(zip(SAMPLES, list(SAMPLE_SHEET["ONT"])))
ONT = {SAMP: READ.split() for SAMP, READ in ONT.items() if READ}
### Pre-run setup ######################################################################
# Build dictionaries of recipes & species to use for alignment
## Dictionary of lists; recipes to use for each sample (short_read module)
RECIPE_DICT = {}
## Dictionary of lists; recipes to use for each sample (ONT module)
RECIPE_ONT_DICT = {}
for i in range(0, SAMPLE_SHEET.shape[0]):
tmp_sample = list(SAMPLE_SHEET["sampleID"])[i]
# short-read-specific dicts
if tmp_sample in R2_FQS.keys():
RECIPE_DICT[tmp_sample] = list(SAMPLE_SHEET["recipe"])[i].split()
# ONT-specific dicts
if tmp_sample in ONT.keys():
if len(ONT[tmp_sample]) > 0:
RECIPE_ONT_DICT[tmp_sample] = list(SAMPLE_SHEET["recipe_ONT"])[i].split()
### recipe_sheet & sample_sheet checks ######################################################################
include: "rules/0_utils.smk"
check_recipe_sheet(RECIPE_SHEET, RECIPE_DICT, RECIPE_ONT_DICT)
check_sample_sheet(SAMPLE_SHEET)
### Wildcard constraints ###############################################################
wildcard_constraints:
OUTDIR=config["OUTDIR"],
SAMPLE="[A-Za-z0-9_-]+",
RECIPE="[A-Za-z0-9_-]+",
### include rules #######################################################################
# Barcode handling ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
include: "rules/0a_barcode_maps.smk"
# Short-read module ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## fastq preprocessing & QC
include: "rules/short_read/1a_mergefqs.smk"
include: "rules/short_read/1b_trimming.smk"
include: "rules/short_read/1c_barcode_calling.smk"
## rRNA Filtering
include: "rules/short_read/2a_rRNA_bwa.smk"
include: "rules/short_read/2b_ribodetector.smk"
include: "rules/short_read/2c_rRNA_qualimap.smk"
## STAR alignment, QC, and post-processing - TODO update numbering
include: "rules/short_read/3a_star_align.smk"
include: "rules/short_read/3b_star_unmapped.smk"
include: "rules/short_read/3c_star_dedup.smk"
include: "rules/short_read/3q_star_qualimap.smk"
include: "rules/short_read/3u_star_uTAR.smk"
## kallisto/bustools alignment
include: "rules/short_read/4a_kbpython.smk"
## small RNA stuff #TODO
include: "rules/short_read/5a_mirge.smk"
include: "rules/short_read/7a_fastqc.smk"
include: "rules/short_read/7b_readqc.smk"
# ONT module ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## preprocessing
include: "rules/ont/1a_preprocessing.smk"
include: "rules/ont/1b_trimming.smk"
include: "rules/ont/1c_barcode_calling.smk"
## alignment
include: "rules/ont/2a_minimap2_genome.smk"
include: "rules/ont/2b_minimap2_transcriptome.smk"
# include: "rules/ont/2c_kallisto-lr.smk"
include: "rules/ont/2d_ultra_genome.smk"
include: "rules/ont/2e_isoquant.smk"
## QC
include: "rules/ont/3a_readqc.smk"
include: "rules/ont/3b_qualimap.smk"
### Build targets #################################################################################
### short-read targets ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Module 1 - preprocessing
## fastQC results
ilmn_fastqc = [
f"{OUTDIR}/{SAMPLE}/short_read/fastqc/{TRIM}_{READ}"
for SAMPLE in R2_FQS.keys()
for TRIM in ["preCutadapt", "postCutadapt", "twiceCutadapt"] # ,"rRNA_bwa","rRNA_STAR"
for READ in ["R1", "R2"]
]
ilmn_barcodes = [
f"{OUTDIR}/{SAMPLE}/short_read/{FILE}"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
for FILE in [
f"barcodes_umis/{RECIPE}/barcodes_corrected.tsv",
f"barcodes_umis/{RECIPE}/bc_correction_stats.txt",
]
]
# Module 2 - rRNA filtering
## alignment QC with qualimap [rRNA alignments]
ilmn_rRNA_qualimap = [
f"{OUTDIR}/{SAMPLE}/short_read/qualimap/rRNA/{TOOL}/{FILE}"
for SAMPLE in R2_FQS.keys()
for TOOL in ["bwa"]
for FILE in [
"rnaseq/report.pdf",
"rnaseq/rnaseq_qc_results.csv",
"bamqc/report.pdf",
"bamqc/genome_results.csv",
]
]
# Module 3 - STAR alignment
## deduped and/or strand-split, umi_tools deduplicated .bam
### STAR count mats
ilmn_STAR_counts = [
f"{OUTDIR}/{SAMPLE}/short_read/STARsolo/{RECIPE}/Solo.out/{SOLO}/raw/{ALGO}.mtx.gz"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
for SOLO in ["Gene", "GeneFull"]
for ALGO in ["UniqueAndMult-EM", "matrix"]
]
### Deduplicated and strand-split alignment files
ilmn_STAR_dedup_bams = [
f"{OUTDIR}/{SAMPLE}/short_read/{REF}/{RECIPE}/Aligned.sortedByCoord.out{STRAND}{STEP}.{FILE}"
for SAMPLE in R2_FQS.keys()
for REF in ["STARsolo"]
for RECIPE in RECIPE_DICT[SAMPLE]
for STRAND in ["", ".fwd", ".rev"]
for STEP in ["", ".dedup"]
for FILE in ["bam", "bam.bai"] # TODO add bigWigs
]
## alignment QC with qualimap | requires deduped input!
ilmn_STAR_qualimap = [
f"{OUTDIR}/{SAMPLE}/short_read/qualimap/{TOOL}/{RECIPE}/{DEDUP}/{FILE}"
for SAMPLE in R2_FQS.keys()
for TOOL in ["STAR"]
for RECIPE in RECIPE_DICT[SAMPLE]
for DEDUP in ["raw"] # , "dedup"
for FILE in [
"rnaseq/report.pdf",
"rnaseq/rnaseq_qc_results.csv",
"bamqc/report.pdf",
"bamqc/genome_results.csv",
]
]
## fastQC results for unmapped reads
ilmn_STAR_unmapped_fastqc = [
f"{OUTDIR}/{SAMPLE}/short_read/fastqc/unmapped/{RECIPE}"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
]
### STAR uTAR outputs
ilmn_STAR_uTAR = [
f"{OUTDIR}/{SAMPLE}/short_read/STARsolo/{RECIPE}/TAR/{FILE}"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
for FILE in ["uTAR.mtx.gz", "qc_plots.png"]
]
# Module 4 - kallisto & bustools
## kallisto-bustools outputs
ilmn_kbpython = [
f"{OUTDIR}/{SAMPLE}/short_read/kbpython_{KB}/{RECIPE}/counts_unfiltered/{FILE}"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
for KB in ["std"] # TODO "nac", "tcc"
for FILE in [
"output.mtx.gz",
"output_genes.tsv.gz",
"output_cells.tsv.gz",
"qc_plots.png",
]
]
# Module 5 - small RNA
## miRge3.0 pseudobulk analysis
ilmn_mirge_bulk = [
f"{OUTDIR}/{SAMPLE}/short_read/miRge_bulk/{RECIPE}/annotation.report.html"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
]
# Module 6 - anndata/scanpy
## anndata and seurat/rds files (with spatial info) - STAR
ilmn_STAR_cache = [
f"{OUTDIR}/{SAMPLE}/short_read/STARsolo/{RECIPE}/Solo.out/{SOLO}/raw/{ALGO}.{FILE}"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
for SOLO in ["Gene", "GeneFull"]
for ALGO in ["UniqueAndMult-EM", "matrix"]
for FILE in ["h5ad", "rds"]
]
## anndata files (with spatial info) - kallisto
ilmn_kb_cache = [
f"{OUTDIR}/{SAMPLE}/short_read/kbpython_{KB}/{RECIPE}/counts_unfiltered/output.{FILE}"
for SAMPLE in R2_FQS.keys()
for RECIPE in RECIPE_DICT[SAMPLE]
for KB in ["std"] # TODO "nac", "tcc"
for FILE in ["h5ad", "rds"]
]
# Module 7 - final QC
# ILMN readqc - custom QC scripts
ilmn_readqc = [
f"{OUTDIR}/{SAMPLE}/short_read/readqc/{TRIM}_qc.{FILE}"
for SAMPLE in R2_FQS.keys()
for READ in ["R1", "R2"]
for RECIPE in RECIPE_DICT[SAMPLE]
for TRIM in [
# f"0_rawInput/{READ}",
# f"1_preCutadapt/{READ}",
# f"2_postCutadapt/{READ}",
# f"3_twiceCutadapt/{READ}",
f"4_aligned/{RECIPE}",
]
for FILE in ["tsv.gz", "png"]
]
### ONT targets ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ont_barcodes = [
f"{OUTDIR}/{SAMPLE}/ont/{FILE}"
for SAMPLE in ONT.keys()
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for FILE in [
f"barcodes_umis/{RECIPE}/barcodes_corrected.tsv",
f"barcodes_umis/{RECIPE}/bc_correction_stats.txt",
]
]
ont_preprocessing_summary = [
f"{OUTDIR}/{SAMPLE}/ont/{FILE}"
for SAMPLE in ONT.keys()
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for FILE in [
f"logs/1a_adapter_scan_summary.csv",
f"plots/1a_adapter_scan_summary.png",
# f"plots/1b_cutadapt_summary.png",
]
]
ont_minimap_genome = [
f"{OUTDIR}/{SAMPLE}/ont/minimap2/{RECIPE}/{FILE}"
for SAMPLE in ONT.keys()
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for FILE in [
f"sorted_filtered_cb_ub_gn.bam",
# "sorted_filtered_cb_ub_gn_pos.bam",
f"raw/output.h5ad",
f"raw/output.rds",
]
]
ont_minimap_txome = [
f"{OUTDIR}/{SAMPLE}/ont/minimap2_txome/{RECIPE}/{FILE}"
for SAMPLE in ONT.keys()
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for FILE in [
f"aligned_filtered_dedup_sorted_cb_ub_xb.bam",
f"oarfish/output.h5ad",
f"oarfish/output.rds",
]
]
ont_ultra_genome = [
f"{OUTDIR}/{SAMPLE}/ont/ultra/{RECIPE}/{FILE}"
for SAMPLE in ONT.keys()
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for FILE in [
f"sorted_filtered_cb_ub.bam",
f"raw/umitools_counts.tsv.gz",
f"raw/output.h5ad",
f"raw/output.rds",
]
]
ont_isoquant = [
f"{OUTDIR}/{SAMPLE}/ont/{ALIGN}/{RECIPE}/{FILE}"
for SAMPLE in ONT.keys()
for ALIGN in ["minimap2", "ultra"]
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for FILE in [
f"sorted_filtered_cb_ub_gn_ig.bam",
f"isoquant/output.h5ad",
f"isoquant/output.rds",
]
]
# ONT readqc - custom QC scripts
ont_readqc = [
f"{OUTDIR}/{SAMPLE}/ont/readqc/{TRIM}_qc.{FILE}"
for SAMPLE in ONT.keys()
for READ in ["R1", "R2"]
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for ALIGN in ["minimap2"] # , "ultra"
for TRIM in [
# f"0_rawInput/merged",
# f"1_preCutadapt/{READ}",
# f"2_postCutadapt/{READ}",
f"3_aligned/{ALIGN}/{RECIPE}",
]
for FILE in ["tsv.gz", "png"]
]
# alignment QC with qualimap
ont_qualimap = [
f"{OUTDIR}/{SAMPLE}/ont/qualimap/{TOOL}/{RECIPE}/{FILE}"
for SAMPLE in ONT.keys()
for RECIPE in RECIPE_ONT_DICT[SAMPLE]
for TOOL in [
"minimap2",
]
for FILE in [
"rnaseq/report.pdf",
"rnaseq/rnaseq_qc_results.csv",
"bamqc/report.pdf",
"bamqc/genome_results.csv",
]
]
# kallisto-lr outputs
# ont_kb = [f"{OUTDIR}/{SAMPLE}/ont/kb/{RECIPE}/{FILE}"
# for SAMPLE in ONT.keys()
# for RECIPE in RECIPE_ONT_DICT[SAMPLE]
# for FILE in [ ]
# ],
### Target rule #################################################################################
rule all:
input:
# ilmn_barcodes,
# ilmn_rRNA_qualimap,
#ilmn_STAR_dedup_bams,
ilmn_STAR_counts,
#ilmn_STAR_qualimap,
# ilmn_STAR_unmapped_fastqc,
# ilmn_STAR_uTAR,
# ilmn_mirge_bulk, #
ilmn_STAR_cache,
#ilmn_kb_cache,
ilmn_fastqc,
ilmn_readqc,
ont_barcodes,
ont_preprocessing_summary,
ont_minimap_genome,
ont_minimap_txome,
ont_ultra_genome,
ont_isoquant,
ont_readqc,
#ont_qualimap,