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- import os
- import yaml
- import pandas as pd
- configfile: "config.yaml"
- ##########################################################
- # 全局变量和样本信息
- ##########################################################
- ## 软件主目录
- PEAKSNAKE_HOME = config["PEAKSNAKE_HOME"] if config["PEAKSNAKE_HOME"] else os.getcwd()
- ## 关键参数
- PEAK_TYPE = config["peak_type"]
- SEQ_TYPE = config["seq_type"]
- PEAK_SELECTION = config["peak_selection"]
- GENOME = config["genome"]
- GTF = config["gtf"]
- ## 样本信息变量
- # 字典:REPLICATE to INPUT
- REPLICATE_TO_INPUT = {k: config['samples'][k] for k in sorted(config['samples'])}
- # 列表:所有 REPLICATES
- REPLICATES = sorted(list(set(REPLICATE_TO_INPUT.keys())))
- # 列表:所有 INPUTS
- INPUTS = sorted(list(set(REPLICATE_TO_INPUT.values())))
- INPUTS = [] if INPUTS == [None] else INPUTS
- # 字典: SAMPLE 与 rep1 rep2 rep2 对应关系
- SAMPLE_TO_REPLICATE = {}
- for s in REPLICATES:
- name, rep = '_'.join(s.split('_')[:-1]), s.split('_')[-1]
- SAMPLE_TO_REPLICATE.setdefault(name, []).append(rep)
- SAMPLE_TO_REPLICATE = {k: sorted(v) for k, v in SAMPLE_TO_REPLICATE.items()}
- ## 生成样本信息表
- with open("sample_sheet.csv", 'w') as f:
- f.write("SampleID,ControlID,Tissue,Factor,Condition,Treatment,Replicate,bamReads,Peaks,bamControl,PeakCaller\n")
- for sample, control in REPLICATE_TO_INPUT.items():
- sample_parts = sample.split('_')
- factor = sample_parts[0] # 提取样本ID中的Factor
- tissue = "NA"
- treatment = sample_parts[1] # 在这个例子中,tissue和condition是相同的
- condition = factor + "_" + treatment
- replicate = sample_parts[2].replace("rep", "") # 将"rep1"和"rep2"转换为"1"和"2"
- if control:
- control_parts = control.split('_')
- control_id = "_".join(control_parts[:2]) # 构建 ControlID
- bamControl = f"clean_bams/{control}_final.bam"
- else:
- control_id = "NA"
- bamControl = "NA"
- bamReads = f"clean_bams/{sample}_final.bam"
- peaks = f"clean_peaks/cutoff/{sample}_peaks.{PEAK_TYPE}Peak"
- f.write(f"{sample},{control_id},{tissue},{factor},{condition},{treatment},{replicate},{bamReads},{peaks},{bamControl},bed\n")
- ##########################################################
- # rule all: 最终想要生成的文件
- ##########################################################
- def get_motifs_from_meme(meme_file):
- motifs = []
- with open(meme_file, 'r') as file:
- for line in file:
- if line.startswith("MOTIF"):
- parts = line.split()
- # 检查是否有三列,且第三列不是空字符串
- if len(parts) == 3 and parts[2]:
- motif_name = parts[2] + "_" + parts[1] # 第三列和第二列的组合
- # 检查是否有两列或第三列为空
- elif len(parts) >= 2:
- motif_name = "_" + parts[1] # 只使用第二列
- motifs.append(motif_name)
- return motifs
- rule all:
- input:
- #####################################
- # 从 fastq 到 peaks
- #####################################
- # 测序数据质控表格
- "quality_control/fastp_summary.tsv",
- # 最终比对结果
- expand("clean_bams/{replicate}_final.bam", replicate = REPLICATES + INPUTS),
- # 比对质控表格
- "quality_control/estimate_read_filtering.tsv",
- # cross correlation 质控表格
- "quality_control/cross_correlation_summary.tsv" if config["cross_correlation"]["do"] else [],
- # bw 文件, deeptools 可视化
- expand("clean_bams/{replicate}.bw", replicate = REPLICATES + INPUTS),
- "deeptools/sample_correlation.pdf" if len(REPLICATES) > 2 else [],
- "deeptools/tss_heatmap.pdf",
- "deeptools/tss_tes_heatmap.pdf",
- # raw peak 结果
- expand("raw_peaks/{replicate}_peaks.{PEAK_TYPE}Peak", replicate = REPLICATES, PEAK_TYPE = PEAK_TYPE),
- # cutoff analysis
- expand("raw_peaks/{replicate}_cutoff_analysis.pdf", replicate = REPLICATES),
- # clean peak 结果
- expand("clean_peaks/cutoff/{replicate}_peaks.{PEAK_TYPE}Peak", replicate = REPLICATES, PEAK_TYPE = PEAK_TYPE),
- # 通过 intersect or idr 进行 peak 筛选
- expand("clean_peaks/{m}/{sample}_peaks.{PEAK_TYPE}Peak", sample=SAMPLE_TO_REPLICATE.keys(), m = PEAK_SELECTION, PEAK_TYPE = PEAK_TYPE),
- # 提取序列
- expand("clean_peaks/{m}/{sample}_peaks.fa", sample=SAMPLE_TO_REPLICATE.keys(), m = PEAK_SELECTION),
- # 所有样本共识peaks
- "clean_peaks/merge/merged_peaks.bed",
- #####################################
- # 定量分析
- #####################################
- "counts/merged_peaks.counts.matrix",
- "counts/merged_peaks.TMM.CPM.matrix",
- #####################################
- # Peak 注释
- #####################################
- # 对单个样本 peaks 注释
- expand("peak_annotation/{sample}_peaks_{hit}.txt", sample = SAMPLE_TO_REPLICATE.keys(), hit = ["allhits", "finalhits"]) if config["uropa"]["do"] else [],
- # 对 merge 之后的 peaks 注释
- expand("peak_annotation/merged_peaks_{hit}.txt", hit = ["allhits", "finalhits"]) if config["uropa"]["do"] else [],
- #####################################
- # 差异分析
- #####################################
- expand("diff_peaks/{contrast}.{m}.DE_results", contrast=config["contrasts"], m=config["diff_peaks"]["method"]) if config["diff_peaks"]["do"] and config["contrasts"] else [],
- #####################################
- # 足迹分析
- #####################################
- "footprinting/bindetect_results.txt" if config["footprint"]["do"] else []
- ##########################################################
- # 使用fastp进行原始数据质控和过滤,自动判断 SE?PE?
- # raw_data => clean_data
- ##########################################################
- rule fastp_quality_control:
- input:
- fastq=["raw_data/{replicate}_R1.fastq.gz", "raw_data/{replicate}_R2.fastq.gz"] if SEQ_TYPE == 'PE' else ["raw_data/{replicate}_R1.fastq.gz"]
- output:
- fastq=["clean_data/{replicate}_R1.fastq.gz", "clean_data/{replicate}_R2.fastq.gz"] if SEQ_TYPE == 'PE' else ["clean_data/{replicate}_R1.fastq.gz"],
- html_report="clean_data/{replicate}_fastp.html",
- json_report="clean_data/{replicate}_fastp.json"
- log: "logs/{replicate}_fastp_quality_control.log"
- threads: 3
- singularity:
- PEAKSNAKE_HOME + "/sifs/commonTools_20231218.sif"
- params:
- fastq="-i raw_data/{replicate}_R1.fastq.gz -o clean_data/{replicate}_R1.fastq.gz -I raw_data/{replicate}_R2.fastq.gz -O clean_data/{replicate}_R2.fastq.gz" if SEQ_TYPE == 'PE' else "-i raw_data/{replicate}_R1.fastq.gz -o clean_data/{replicate}_R1.fastq.gz",
- fastp=config["fastp"]
- shell:
- """
- fastp {params.fastq} --html {output.html_report} --json {output.json_report} --thread {threads} {params.fastp} 1>{log} 2>&1
- """
- ##########################################################
- # 根据基因组构建 bowtie2 index
- ##########################################################
- rule bowtie2_build:
- input:
- genome = GENOME
- output:
- index_prefix = "ref/genome.1.bt2"
- log: "logs/bowtie2_build.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/bowtie2_2.5.2.sif"
- threads: 6
- shell:
- "bowtie2-build --threads {threads} {input.genome} ref/genome 1>{log} 2>&1"
- ##########################################################
- # 使用 bowtie2 将测序数据比对到参考基因组
- # fastq => sam
- ##########################################################
- rule bowtie2_align:
- input:
- fastq=["clean_data/{replicate}_R1.fastq.gz", "clean_data/{replicate}_R2.fastq.gz"] if SEQ_TYPE == 'PE' else ["clean_data/{replicate}_R1.fastq.gz"],
- genome_index=config["bowtie2_index"] + ".1.bt2" if config["bowtie2_index"] else "ref/genome.1.bt2"
- output:
- sam="raw_bams/{replicate}.sam"
- log: "logs/{replicate}_bowtie2_align.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/bowtie2_2.5.2.sif"
- threads: 4
- params:
- genome_index=config["bowtie2_index"] if config["bowtie2_index"] else "ref/genome",
- fastq="-1 clean_data/{replicate}_R1.fastq.gz -2 clean_data/{replicate}_R2.fastq.gz" if SEQ_TYPE == 'PE' else "-U clean_data/{replicate}_R1.fastq.gz",
- bowtie2=config["bowtie2"] if config["bowtie2"] else ""
- shell:
- """
- bowtie2 -p {threads} -x {params.genome_index} {params.fastq} -S {output.sam} {params.bowtie2} 1>{log} 2>&1
- """
- rule sort_bam:
- input:
- sam="raw_bams/{replicate}.sam"
- output:
- sorted_bam="raw_bams/{replicate}_sorted.bam"
- log: "logs/{replicate}_sort_bam.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/commonTools_20231218.sif"
- threads: 4
- shell:
- """
- samtools sort -@ {threads} -o {output.sorted_bam} {input.sam} 1>{log} 2>&1
- samtools index {output.sorted_bam}
- """
- rule sieve_alignment:
- input:
- bam="raw_bams/{replicate}_sorted.bam"
- output:
- bam="clean_bams/{replicate}_final.bam"
- log: "logs/{replicate}_sieve_alignment.log"
- threads: 4
- singularity:
- PEAKSNAKE_HOME + "/sifs/deeptools_20231220.sif"
- params:
- peaksnake_home=PEAKSNAKE_HOME,
- minMappingQuality=config["alignmentSieve"]["minMappingQuality"],
- blacklist="--blackListFileName " + config["alignmentSieve"]["blacklist"] if config["alignmentSieve"]["blacklist"] else [],
- extra=config["alignmentSieve"]["extra"] if config["alignmentSieve"]["extra"] else ""
- shell:
- """
- alignmentSieve --numberOfProcessors {threads} --bam {input.bam} --outFile {output.bam} --filterMetrics {log} --ignoreDuplicates --minMappingQuality {params.minMappingQuality} --samFlagExclude 260 {params.blacklist} {params.extra} 1>{log} 2>&1
-
- samtools index {output.bam}
- """
- rule estimate_read_filtering:
- input:
- bams=expand("raw_bams/{replicate}_sorted.bam", replicate=REPLICATES + INPUTS)
- output:
- stat="quality_control/estimate_read_filtering.tsv"
- threads: 4
- singularity:
- PEAKSNAKE_HOME + "/sifs/deeptools_20231220.sif"
- log: "logs/estimate_read_filtering.log"
- params:
- peaksnake_home=PEAKSNAKE_HOME,
- minMappingQuality=config["alignmentSieve"]["minMappingQuality"],
- blacklist="--blackListFileName " + config["alignmentSieve"]["blacklist"] if config["alignmentSieve"]["blacklist"] else "",
- extra=config["alignmentSieve"]["extra"] if config["alignmentSieve"]["extra"] else "",
- sampleLabels=REPLICATES + INPUTS
- shell:
- """
- estimateReadFiltering \
- --numberOfProcessors {threads} \
- --bam {input.bams} \
- --sampleLabels {params.sampleLabels} \
- --outFile {output.stat} \
- --ignoreDuplicates \
- --minMappingQuality {params.minMappingQuality} \
- --samFlagExclude 260 \
- {params.blacklist} \
- {params.extra} 1>{log} 2>&1
- """
- ##########################################################
- # DeepTools 绘图
- ##########################################################
- rule convert_bam_to_bigwig:
- input:
- bam="clean_bams/{replicate}_final.bam"
- output:
- bw="clean_bams/{replicate}.bw"
- log: "logs/{replicate}_convert_bam_to_bigwig.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/deeptools_20231220.sif"
- threads: 2
- params:
- gsize=config["gsize"],
- bamCoverage = config["bamCoverage"] if config["bamCoverage"] else ""
- shell:
- """
- bamCoverage -p {threads} --bam {input.bam} -o {output.bw} --effectiveGenomeSize {params.gsize} {params.bamCoverage} 1>{log} 2>&1
- """
- rule summarize_multiple_bigwigs:
- input:
- bws=expand("clean_bams/{replicate}.bw", replicate=REPLICATES + INPUTS),
- tss_tes_bed=config["tss_tes_bed"]
- output:
- "clean_bams/bw_summary.gz"
- params:
- labels=REPLICATES + INPUTS
- log: "logs/summarize_multiple_bigwigs.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/deeptools_20231220.sif"
- threads: 10
- shell:
- """
- multiBigwigSummary BED-file \
- --bwfiles {input.bws} \
- --labels {params.labels} \
- --BED {input.tss_tes_bed} \
- -o {output} -p {threads} 1>{log} 2>&1
- """
- rule generate_correlation_plots:
- input:
- "clean_bams/bw_summary.gz"
- output:
- pdf="deeptools/sample_correlation.pdf",
- tab="deeptools/sample_correlation.tab"
- log: "logs/generate_correlation_plots.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/deeptools_20231220.sif"
- shell:
- """
- plotCorrelation -in {input} -o {output.pdf} \
- --corMethod pearson --whatToPlot heatmap \
- -min 0.5 \
- --plotTitle "Pearson Correlation of Samples" \
- --outFileCorMatrix {output.tab} 1>{log} 2>&1
- """
- rule plot_heatmap_reference_point:
- input:
- bws=expand("clean_bams/{replicate}.bw", replicate=REPLICATES + INPUTS),
- tss_tes_bed=config["tss_tes_bed"],
- tss_tes_shuffle_bed=config["tss_tes_shuffle_bed"]
- output:
- tss_matrix="deeptools/tss_matrix.gz",
- tss_heatmap="deeptools/tss_heatmap.pdf"
- params:
- labels=REPLICATES + INPUTS
- log: "logs/plot_heatmap_reference_point.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/deeptools_20231220.sif"
- threads: 10
- shell:
- """
- computeMatrix reference-point \
- -S {input.bws} \
- --samplesLabel {params.labels} \
- -R {input.tss_tes_bed} {input.tss_tes_shuffle_bed} \
- --referencePoint TSS \
- -b 5000 -a 5000 \
- --binSize 50 \
- -o {output.tss_matrix} \
- -p {threads} 1>{log} 2>&1
-
- plotHeatmap -m {output.tss_matrix} -o {output.tss_heatmap} --missingDataColor 0.5 1>>{log} 2>&1
- """
- rule plot_heatmap_scale_regions:
- input:
- bws=expand("clean_bams/{replicate}.bw", replicate=REPLICATES + INPUTS),
- tss_tes_bed=config["tss_tes_bed"],
- tss_tes_shuffle_bed=config["tss_tes_shuffle_bed"]
- output:
- tss_tes_matrix="deeptools/tss_tes_matrix.gz",
- tss_tes_heatmap="deeptools/tss_tes_heatmap.pdf"
- params:
- labels=REPLICATES + INPUTS
- log: "logs/plot_heatmap_scale_regions.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/deeptools_20231220.sif"
- threads: 10
- shell:
- """
- computeMatrix scale-regions \
- -S {input.bws} \
- --samplesLabel {params.labels} \
- -R {input.tss_tes_bed} {input.tss_tes_shuffle_bed} \
- --regionBodyLength 4000 \
- -b 2000 -a 2000 \
- --binSize 50 \
- -o {output.tss_tes_matrix} \
- -p {threads} 1>{log} 2>&1
- plotHeatmap -m {output.tss_tes_matrix} -o {output.tss_tes_heatmap} --missingDataColor 0.5 1>>{log} 2>&1
- """
- ##########################################################
- # 对每个 replicate:input call peak
- ##########################################################
- # 规则:MACS3 call peak
- rule callpeak_with_macs3:
- input:
- sorted_ip_bam="clean_bams/{replicate}_final.bam",
- sorted_input_bam=lambda wildcards: f"clean_bams/{config['samples'][wildcards.replicate]}_final.bam" if config['samples'][wildcards.replicate] else []
- output:
- Peak="raw_peaks/{replicate}_peaks." + PEAK_TYPE + "Peak",
- cutoff_analysis_txt="raw_peaks/{replicate}_cutoff_analysis.txt"
- log: "logs/{replicate}_callpeak_with_macs3.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/macs3_idr_20231218.sif"
- threads: 1
- params:
- control=lambda wildcards: f"-c clean_bams/{config['samples'][wildcards.replicate]}_final.bam" if config['samples'][wildcards.replicate] else "",
- format="BAMPE" if SEQ_TYPE == 'PE' and '--nomodel' not in config["macs3"]["extra"] else "BAM",
- gsize=config["gsize"],
- PEAK_TYPE="--broad" if PEAK_TYPE == "broad" else "",
- extra = config["macs3"]["extra"] if config["macs3"]["extra"] else ""
- shell:
- """
- macs3 callpeak -g {params.gsize} -t {input.sorted_ip_bam} {params.control} --name raw_peaks/{wildcards.replicate} --format {params.format} --keep-dup all --qvalue 0.075 --cutoff-analysis {params.PEAK_TYPE} {params.extra} 1>{log} 2>&1
- """
- rule plot_macs_cutoff_analysis:
- input:
- cutoff_analysis_txt="raw_peaks/{replicate}_cutoff_analysis.txt"
- output:
- cutoff_analysis_pdf="raw_peaks/{replicate}_cutoff_analysis.pdf"
- log: "logs/{replicate}_plot_macs_cutoff_analysis.log"
- shell:
- """
- python {PEAKSNAKE_HOME}/scripts/plot_macs_cutoff_analysis.py {input.cutoff_analysis_txt} {output} 1>{log} 2>&1
- """
- rule filter_peaks_by_qscore:
- input:
- Peak="raw_peaks/{replicate}_peaks." + PEAK_TYPE + "Peak"
- output:
- Peak="clean_peaks/cutoff/{replicate}_peaks." + PEAK_TYPE + "Peak"
- params:
- qscore=config["macs3"]["qscore"]
- shell:
- """
- awk '$9>{params.qscore}' {input.Peak} > {output.Peak}
- """
- rule select_peaks_norep:
- input:
- Peak="clean_peaks/cutoff/{sample}_rep1_peaks." + PEAK_TYPE + "Peak"
- output:
- Peak="clean_peaks/norep/{sample}_peaks." + PEAK_TYPE + "Peak"
- shell:
- """
- cp {input.Peak} {output.Peak}
- """
- rule select_peaks_by_intersect:
- input:
- Peak=lambda wildcards: expand("clean_peaks/cutoff/" + wildcards.sample + "_{rep}_peaks." + PEAK_TYPE + "Peak", rep=SAMPLE_TO_REPLICATE[wildcards.sample])
- output:
- Peak="clean_peaks/intersect/{sample}_peaks." + PEAK_TYPE + "Peak"
- params:
- min_overlap=config['intersect']['min_overlap']
- shell:
- """
- # 检查输入文件的数量
- num_peaks=$(echo {input.Peak} | wc -w)
- # 如果只有一个输入文件
- if [ "$num_peaks" -eq 1 ]; then
- cp {input.Peak[0]} {output.Peak}
- else
- # 复制第一个输入文件到临时文件
- cp {input.Peak[0]} {wildcards.sample}.temp.bed
- # 使用除第一个之外的所有输入文件
- echo {input.Peak} | tr ' ' '\\n' | awk 'NR>1' | while read bed; do
- bedtools intersect -f {params.min_overlap} -r -a {wildcards.sample}.temp.bed -b $bed -wa > {wildcards.sample}.temp2.bed
- mv {wildcards.sample}.temp2.bed {wildcards.sample}.temp.bed
- done
- # 创建一个中间的 peak list 文件
- cut -f 4 {wildcards.sample}.temp.bed > {wildcards.sample}.peak_lst
- # 使用中间的 peak list 文件和第一个输入文件生成最终输出
- awk 'NR==FNR {{a[$1]; next}} $4 in a' {wildcards.sample}.peak_lst {input.Peak[0]} > {output.Peak}
- # 清理临时文件
- rm {wildcards.sample}.temp.bed {wildcards.sample}.peak_lst
- fi
- """
- rule select_peaks_by_idr:
- input:
- rep1_peaks="raw_peaks/{sample}_rep1_peaks." + PEAK_TYPE + "Peak",
- rep2_peaks="raw_peaks/{sample}_rep2_peaks." + PEAK_TYPE + "Peak"
- output:
- true_rep_idr="clean_peaks/idr/{sample}_true_rep_idr.txt",
- idr_peaks="clean_peaks/idr/{sample}_peaks." + PEAK_TYPE + "Peak"
- log: "logs/{sample}_select_peaks_by_idr.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/macs3_idr_20231218.sif"
- threads: 1
- params:
- PEAK_TYPE=PEAK_TYPE,
- idr_threshold=config["idr"]["idr_threshold"]
- shell:
- """
- idr --samples {input.rep1_peaks} {input.rep2_peaks} --idr-threshold {params.idr_threshold} --output-file {output.true_rep_idr} --plot --input-file-type {PEAK_TYPE}Peak --rank p.value 1>{log} 2>&1
- awk -v OFS="\\t" 'BEGIN {{FS=OFS}} {{ $4=$1":"$2"_"$3; print $1, $2, $3, $4, $5, $6, $7, $8, $9, $10 }}' {output.true_rep_idr} | sort -k1,1 -k2,2n -k3,3n > {output.idr_peaks}
- """
- ##########################################################
- # 提取序列
- ##########################################################
- rule extract_peak_sequence:
- input:
- Peak="clean_peaks/{m}/{sample}_peaks." + PEAK_TYPE + "Peak"
- output:
- peak_fa="clean_peaks/{m}/{sample}_peaks.fa"
- params:
- top_n=config["motif"]["top_n"],
- summit_flank=config["motif"]["summit_flank"],
- genome=config["genome"],
- summit_fa="clean_peaks/{m}/{sample}_summit.fa"
- shell:
- """
- set +o pipefail;
- # Sorting and extracting fasta for peak
- sort -k8,8nr {input.Peak} | head -n {params.top_n} | bedtools getfasta -fi {params.genome} -bed - > {output.peak_fa}
- # Handling narrow peaks
- if [[ "{PEAK_TYPE}" == "narrow" ]]; then
- sort -k8,8nr {input.Peak} | head -n {params.top_n} | awk -v OFS='\\t' -v flank={params.summit_flank} '{{print $1, $2+$10-flank, $2+$10+flank+1}}' | awk '$2>=0' | bedtools getfasta -fi {params.genome} -bed - > {params.summit_fa}
- fi
- """
- ##########################################################
- # Peak 注释
- ##########################################################
- rule peak_annotation_with_uropa:
- input:
- Peak="clean_peaks/" + PEAK_SELECTION + "/{sample}_peaks." + PEAK_TYPE + "Peak",
- gtf=config["gtf"]
- output:
- allhits="peak_annotation/{sample}_peaks_allhits.txt",
- finalhits="peak_annotation/{sample}_peaks_finalhits.txt"
- log: "logs/{sample}_peak_annotation_with_uropa.log"
- params:
- feature=config["uropa"]["feature"],
- feature_anchor=config["uropa"]["feature_anchor"],
- distance=config["uropa"]["distance"],
- relative_location=config["uropa"]["relative_location"]
- singularity:
- PEAKSNAKE_HOME + "/sifs/uropa_4.0.3--pyhdfd78af_0.sif"
- shell:
- """
- uropa --bed {input.Peak} --gtf {input.gtf} --feature {params.feature} --feature-anchor {params.feature_anchor} --distance {params.distance} --relative-location {params.relative_location} --show-attributes gene_id --outdir peak_annotation 1>{log} 2>&1
- """
- ##########################################################
- # 生成所有 samples 共识 peaks
- ##########################################################
- rule merge_peaks:
- input:
- sample_peaks=expand("clean_peaks/" + PEAK_SELECTION + "/{sample}_peaks." + PEAK_TYPE + "Peak", sample=SAMPLE_TO_REPLICATE.keys())
- output:
- merged_peaks_bed="clean_peaks/merge/merged_peaks.bed",
- merged_peaks_saf="clean_peaks/merge/merged_peaks.saf"
- singularity:
- PEAKSNAKE_HOME + "/sifs/commonTools_20231218.sif"
- params:
- fai=config['genome'] + ".fai"
- shell:
- """
- mkdir -p clean_peaks/merge
- cat {input.sample_peaks} > clean_peaks/merge/cat_peaks.bed
- bedtools sort -i clean_peaks/merge/cat_peaks.bed -g {params.fai} > clean_peaks/merge/cat_sorted_peaks.bed
- bedtools merge -i clean_peaks/merge/cat_sorted_peaks.bed > {output.merged_peaks_bed}
- awk 'OFS="\t" {{print $1":"$2"-"$3, $1, $2+1, $3, "."}}' {output.merged_peaks_bed} > {output.merged_peaks_saf}
- """
- rule merged_peak_annotation_with_uropa:
- input:
- Peak="clean_peaks/merge/merged_peaks.bed",
- gtf=config["gtf"]
- output:
- allhits="peak_annotation/merged_peaks_allhits.txt",
- finalhits="peak_annotation/merged_peaks_finalhits.txt"
- log: "logs/merged_peak_annotation_with_uropa.log"
- params:
- feature=config["uropa"]["feature"],
- feature_anchor=config["uropa"]["feature_anchor"],
- distance=config["uropa"]["distance"],
- relative_location=config["uropa"]["relative_location"]
- singularity:
- PEAKSNAKE_HOME + "/sifs/uropa_4.0.3--pyhdfd78af_0.sif"
- shell:
- """
- uropa --bed {input.Peak} --gtf {input.gtf} --feature {params.feature} --feature-anchor {params.feature_anchor} --distance {params.distance} --relative-location {params.relative_location} --show-attributes gene_id --outdir peak_annotation 1>{log} 2>&1
- """
- ##########################################################
- # 使用 feature counts 计算 replicate peak counts
- ##########################################################
- rule run_feature_counts:
- input:
- bam="clean_bams/{replicate}_final.bam",
- merged_peaks_saf="clean_peaks/merge/merged_peaks.saf"
- output:
- counts="counts/{replicate}.count",
- stat="counts/{replicate}.log"
- log: "logs/{replicate}_run_feature_counts.log"
- params:
- peaksnake_home=PEAKSNAKE_HOME,
- isPairedEnd="TRUE" if SEQ_TYPE == 'PE' else "FALSE"
- shell:
- """
- Rscript {params.peaksnake_home}/software/RunFeatureCounts/run-featurecounts.R -b {input.bam} --saf {input.merged_peaks_saf} --isPairedEnd {params.isPairedEnd} -o counts/{wildcards.replicate} 1>{log} 2>&1
- """
- ##########################################################
- # 合并生成 replicate counts 矩阵
- ##########################################################
- rule create_count_matrix:
- input:
- expand("counts/{replicate}.count", replicate=REPLICATES)
- output:
- counts_matrix="counts/merged_peaks.counts.matrix",
- cpm_matrix="counts/merged_peaks.TMM.CPM.matrix"
- log: "logs/create_count_matrix.log"
- params:
- peaksnake_home=PEAKSNAKE_HOME
- shell:
- """
- ls {input} >counts/count.fofn
- perl {params.peaksnake_home}/software/RunFeatureCounts/abundance_estimates_to_matrix.pl --est_method featureCounts --quant_files counts/count.fofn --out_prefix counts/merged_peaks 1>{log} 2>&1
- """
- ##########################################################
- # 使用 DESeq2/ edgeR 进行差异分析
- ##########################################################
- if config["contrasts"]:
- # 生成 samples.txt
- with open('samples.txt', 'w') as file:
- for ip in REPLICATES:
- # 提取 sample name
- sample_name = '_'.join(ip.split('_')[:2])
- file.write(f"{sample_name}\t{ip}\n")
- # 生成 contrasts.txt
- with open("contrasts.txt", "w") as file:
- file.write("\n".join([" ".join(item.split("_vs_")) for item in config["contrasts"]]))
- rule run_deseq2:
- input:
- "counts/merged_peaks.counts.matrix"
- output:
- expand("diff_peaks/{contrast}.DESeq2.DE_results", contrast=config["contrasts"])
- log: "logs/run_deseq2.log"
- params:
- extra=config["diff_peaks"]["extra"]
- singularity:
- PEAKSNAKE_HOME + "/sifs/trinity_20231218.sif"
- shell:
- """
- run_DE_analysis.pl -m {input} --method DESeq2 -s samples.txt --contrasts contrasts.txt -o diff_peaks {params.extra} 1>{log} 2>&1
- cd diff_peaks/
- rm *count_matrix *.MA_n_Volcano.pdf *.Rscript
- for file in merged_peaks.counts.matrix.*.DE_results; do
- echo -e "PeakID\tsampleA\tsampleB\tlog2FoldChange\tPValue\tPadj" >"${{file#merged_peaks.counts.matrix.}}"
- grep -v "^sampleA" $file | awk 'BEGIN {{OFS="\t"}} {{print $1,$2,$3,$7,$10,$11}}' >> "${{file#merged_peaks.counts.matrix.}}"
- rm $file
- done
- cd ..
- """
- rule run_edgeR:
- input:
- "counts/merged_peaks.counts.matrix"
- output:
- expand("diff_peaks/{contrast}.edgeR.DE_results", contrast=config["contrasts"])
- log: "logs/run_edgeR.log"
- params:
- extra=config["diff_peaks"]["extra"]
- singularity:
- PEAKSNAKE_HOME + "/sifs/trinity_20231218.sif"
- shell:
- """
- run_DE_analysis.pl -m {input} --method edgeR -s samples.txt --contrasts contrasts.txt -o diff_peaks {params.extra} 1>{log} 2>&1
- cd diff_peaks/
- rm *count_matrix *.MA_n_Volcano.pdf *.Rscript
- for file in merged_peaks.counts.matrix.*.DE_results; do
- echo -e "PeakID\tsampleA\tsampleB\tlog2FoldChange\tPValue\tPadj" >"${{file#merged_peaks.counts.matrix.}}"
- grep -v "^sampleA" $file | awk 'BEGIN {{OFS="\t"}} {{print $1,$2,$3,$4,$6,$7}}' >> "${{file#merged_peaks.counts.matrix.}}"
- rm $file
- done
- cd ..
- """
- ##########################################################
- # 合并fastp质控结果生成表格
- ##########################################################
- rule combine_fastp_reports:
- input:
- expand("clean_data/{replicate}_fastp.json", replicate=REPLICATES + INPUTS)
- output:
- "quality_control/fastp_summary.tsv"
- log: "logs/combine_fastp_reports.log"
- params:
- peaksnake_home=PEAKSNAKE_HOME
- shell:
- """
- Rscript {params.peaksnake_home}/scripts/combine_fastp_report.R --input {input} --output quality_control/ 1>{log} 2>&1
- """
- ##########################################################
- # 使用 TOBIAS 进行足迹分析
- ##########################################################
- rule merge_replicate_bams:
- input:
- bams=lambda wildcards: expand("clean_bams/{sample}_{rep}_final.bam", sample = wildcards.sample, rep=SAMPLE_TO_REPLICATE[wildcards.sample])
- output:
- bam="clean_bams/{sample}_merged.bam"
- shell:
- """
- samtools merge -o {output.bam} {input.bams}
- samtools index {output.bam}
- """
- rule ATACorrect:
- input:
- bam="clean_bams/{sample}_merged.bam",
- genome=config["genome"],
- merged_peaks_bed="clean_peaks/merge/merged_peaks.bed"
- output:
- bw="footprinting/{sample}_corrected.bw"
- params:
- prefix="{sample}"
- threads: 8
- log: "logs/{sample}_ATACorrect.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/tobias_20231231.sif"
- shell:
- """
- TOBIAS ATACorrect --bam {input.bam} --genome {input.genome} --peaks {input.merged_peaks_bed} --outdir footprinting --prefix {params.prefix} --cores {threads} 1>{log} 2>&1
- """
- rule FootprintScores:
- input:
- bw="footprinting/{sample}_corrected.bw",
- merged_peaks_bed="clean_peaks/merge/merged_peaks.bed"
- output:
- bw="footprinting/{sample}_footprints.bw"
- params:
- prefix={sample}
- threads: 8
- log: "logs/{sample}_FootprintScores.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/tobias_20231231.sif"
- shell:
- """
- TOBIAS ScoreBigwig --signal {input.bw} --regions {input.merged_peaks_bed} --output {output.bw} --cores {threads} 1>{log} 2>&1
- """
- rule BINDetect:
- input:
- bws=expand("footprinting/{sample}_footprints.bw", sample=SAMPLE_TO_REPLICATE.keys()),
- merged_peaks_bed="clean_peaks/merge/merged_peaks.bed",
- genome=config["genome"]
- output:
- "footprinting/bindetect_results.txt",
- expand("footprinting/{motif}/beds/{motif}_all.bed", motif=get_motifs_from_meme(config["footprint"]["motif"])),
- expand("footprinting/{motif}/beds/{motif}_{sample}_{b}.bed", motif=get_motifs_from_meme(config["footprint"]["motif"]), sample=SAMPLE_TO_REPLICATE.keys(), b=["bound", "unbound"])
- params:
- samples=" ".join(SAMPLE_TO_REPLICATE.keys()),
- motif_databases=config["footprint"]["motif"]
- threads: 8
- log: "logs/BINDetect.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/tobias_20231231.sif"
- shell:
- """
- TOBIAS BINDetect --motifs {params.motif_databases} --signals {input.bws} --genome {input.genome} --peaks {input.merged_peaks_bed} --outdir footprinting --cond_names {params.samples} --cores {threads} 1>{log} 2>&1
- """
- ##########################################################
- # cross correlation
- ##########################################################
- rule cross_correlation:
- input:
- bam="clean_bams/{replicate}_final.bam"
- output:
- pdf="quality_control/cross_correlation/{replicate}.pdf",
- tsv="quality_control/cross_correlation/{replicate}.tsv"
- log: "logs/{replicate}_cross_correlation.log"
- singularity:
- PEAKSNAKE_HOME + "/sifs/phantompeakqualtools_20231218.sif"
- params:
- spp=config['cross_correlation']['spp'] if config['cross_correlation']['spp'] else ""
- threads: 4
- shell:
- """
- run_spp.R -p={threads} -c={input.bam} -savp={output.pdf} -out={output.tsv} -rf {params.spp} 1>{log} 2>&1
- """
- rule cross_correlation_summary:
- input:
- expand("quality_control/cross_correlation/{replicate}.tsv", replicate=REPLICATES + INPUTS)
- output:
- "quality_control/cross_correlation_summary.tsv"
- shell:
- """
- echo -e "Sample\\tTotalReadsFiltered\\tFragmentLength\\tCrossCorrelation\\tPhantomPeakLocation\\tPhantomPeakCorrelation\\tMinimumCrossCorrelationShift\\tMinimumCrossCorrelationValue\\tNSC\\tRSC\\tPhantomPeakQualityTag" >{output}
- cat {input} | sort -k 1 >>{output}
- """
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