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feat: initial optional steps commit
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@mihirsamdarshi
mihirsamdarshi committed Jul 18, 2023
1 parent ef2e853 commit 52210ef
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Showing 4 changed files with 139 additions and 101 deletions.
10 changes: 5 additions & 5 deletions wdl/collect_qc_metrics/collect_qc.wdl
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Original file line number Diff line number Diff line change
Expand Up @@ -9,12 +9,12 @@ task rnaseqQC {

String docker

File trim_summary
File mapped_report
File rRNA_report
File globin_report
File phix_report
File umi_report
File? trim_summary
File? umi_report
File star_log
String SID
}
Expand All @@ -33,13 +33,13 @@ task rnaseqQC {
--sample ~{SID} \
--multiqc_prealign multiQC_prealign_report \
--multiqc_postalign multiQC_postalign_report \
--cutadapt_report ~{trim_summary} \
--mapped_report ~{mapped_report} \
--rRNA_report ~{rRNA_report} \
--globin_report ~{globin_report} \
--phix_report ~{phix_report} \
--umi_report ~{umi_report} \
--star_log ~{star_log}
--star_log ~{star_log} \
~{"--umi_report " + umi_report} \
~{"--cutadapt_report " + trim_summary}

touch ~{SID}_qc_info.csv

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94 changes: 52 additions & 42 deletions wdl/collect_qc_metrics/rnaseq_qc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,8 @@
pipeline
Usage : python rnaseq_qc.py --multiqc_prealign multiQC_prealign_report --multiqc_postalign
multiQC_postalign_report 8019468197_summary.txt 8019468197_mapped_report.txt
8019468197_rRNA_report.txt 8019468197_globin_report.txt 8019468197_phix_report.txt
multiQC_postalign_report 8019468197_summary.txt 8019468197_mapped_report.txt
8019468197_rRNA_report.txt 8019468197_globin_report.txt 8019468197_phix_report.txt
8019468197_umi_report.txt 8019468197.Log.final.out
Author : Archana Raja
Expand All @@ -22,13 +22,13 @@ def make_args():
parser.add_argument("--sample", help="Sample prefix")
parser.add_argument("--multiqc_prealign", help="path to MultiQC prealign directory")
parser.add_argument("--multiqc_postalign", help="path to MultiQC postalign directory")
parser.add_argument("--cutadapt_report", help="Cutadapt report file")
parser.add_argument("--mapped_report", help="Alignment report")
parser.add_argument("--rRNA_report", help="rRNA alignment report")
parser.add_argument("--globin_report", help="globin alignment report")
parser.add_argument("--phix_report", help="phix alignment report")
parser.add_argument("--umi_report", help="UMI duplication report")
parser.add_argument("--star_log", help="STAR log file")
parser.add_argument("--umi_report", help="UMI duplication report", required=False)
parser.add_argument("--cutadapt_report", help="Cutadapt report file", required=False)
return parser.parse_args()


Expand All @@ -54,8 +54,17 @@ def main():
df_pa = pd.read_csv(mqc_gen, sep="\t", header=0)
df_star_log = pd.read_csv(args.star_log, index_col=0, sep="\t")
df_rna_metrics = pd.read_csv(mqc_rna_metrics, sep="\t", header=0)
df_cutadapt = pd.read_csv(args.cutadapt_report, sep="\t", header=0)
df_umi = pd.read_csv(args.umi_report, sep="\t", header=0)

if args.cutadapt_report:
df_cutadapt = pd.read_csv(args.cutadapt_report, sep="\t", header=0)
else:
df_cutadapt = None

if args.umi_report:
df_umi = pd.read_csv(args.umi_report, sep="\t", header=0)
else:
df_umi = None

df_globin = pd.read_csv(args.globin_report, sep="\t", header=0)
df_r_rna = pd.read_csv(args.rRNA_report, sep="\t", header=0)
df_phix = pd.read_csv(args.phix_report, sep="\t", header=0)
Expand All @@ -67,34 +76,33 @@ def main():
print("Success creating data frames")

# %trimmed_bases
percent_trimmed_bases = df_raw[
"Cutadapt_mqc-generalstats-cutadapt-percent_trimmed"
][0].round(3)
percent_trimmed_bases = df_raw["Cutadapt_mqc-generalstats-cutadapt-percent_trimmed"][0].round(3)

# %Adapter detected
pct_adapter_detected = df_cutadapt["pct_adapter_detected"][0]
if df_cutadapt is not None:
# %Adapter detected
pct_adapter_detected = df_cutadapt["pct_adapter_detected"][0]

# get mean raw read count
reads_raw = (
df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][1]
+ df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][2]
) / 2
df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][1]
+ df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][2]
) / 2

# Below expression extracts the sample_name by splitting the first value in the
# Sample column by _R1.fastq.gz or _R2.fastq.gz
sample_name = re.split("_R[1,2]", (df_raw["Sample"][0]))[0]

# get read counts after trimming (reads)
reads_trim = (
df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][3]
+ df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][4]
) / 2
df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][3]
+ df_raw["FastQC_mqc-generalstats-fastqc-total_sequences"][4]
) / 2

# get GC content of the trimmed reads (%GC)
gc = (
df_raw["FastQC_mqc-generalstats-fastqc-percent_gc"][3]
+ df_raw["FastQC_mqc-generalstats-fastqc-percent_gc"][4]
) / 2
df_raw["FastQC_mqc-generalstats-fastqc-percent_gc"][3]
+ df_raw["FastQC_mqc-generalstats-fastqc-percent_gc"][4]
) / 2

# %dup_sequence
dup_seq = (
Expand Down Expand Up @@ -122,8 +130,9 @@ def main():
(df_pa["Picard_mqc-generalstats-picard-PERCENT_DUPLICATION"][0]) * 100
).round(3)

# UMI dup percent
pct_umi_dup = df_umi["pct_umi_dup"][0]
if df_umi is not None:
# UMI dup percent
pct_umi_dup = df_umi["pct_umi_dup"][0]

# % chimeric reads
d = df_star_log.to_dict()
Expand All @@ -134,7 +143,6 @@ def main():
data1 = {
"Sample": [sample_name],
"reads_raw": [reads_raw],
"pct_adapter_detected": [pct_adapter_detected],
"pct_trimmed": [perc_trimmed],
"pct_trimmed_bases": [percent_trimmed_bases],
"reads": [reads_trim],
Expand All @@ -144,9 +152,14 @@ def main():
"pct_globin": [perc_globin],
"pct_phix": [perc_phix],
"pct_picard_dup": [perc_picard_dup],
"pct_umi_dup": [pct_umi_dup],
}

if df_cutadapt is not None:
data1["pct_adapter_detected"] = [pct_adapter_detected]

if df_umi is not None:
data1["pct_umi_dup"] = [pct_umi_dup]

df1 = pd.DataFrame(data1)
df1["Sample"] = df1.Sample.astype("str")
print("df_prealign")
Expand Down Expand Up @@ -209,17 +222,17 @@ def main():

# Modifying rnaseqmetrics data frame column names
df_rna_metrics = df_rna_metrics.loc[
:,
[
"Sample",
"PCT_CODING_BASES",
"PCT_MRNA_BASES",
"PCT_INTRONIC_BASES",
"MEDIAN_5PRIME_TO_3PRIME_BIAS",
"PCT_INTERGENIC_BASES",
"PCT_UTR_BASES",
],
]
:,
[
"Sample",
"PCT_CODING_BASES",
"PCT_MRNA_BASES",
"PCT_INTRONIC_BASES",
"MEDIAN_5PRIME_TO_3PRIME_BIAS",
"PCT_INTERGENIC_BASES",
"PCT_UTR_BASES",
],
]
df_rna_metrics = df_rna_metrics.reindex(
[
"Sample",
Expand All @@ -232,11 +245,8 @@ def main():
],
axis=1,
)
df_rna_metrics.columns = [x.strip().replace("_BASES", "") for x in
df_rna_metrics.columns]
df_rna_metrics.rename(
columns={"MEDIAN_5PRIME_TO_3PRIME_BIAS": "median_5_3_bias"}, inplace=True
)
df_rna_metrics.columns = [x.strip().replace("_BASES", "") for x in df_rna_metrics.columns]
df_rna_metrics.rename(columns={"MEDIAN_5PRIME_TO_3PRIME_BIAS": "median_5_3_bias"}, inplace=True)
df_rna_metrics.columns = df_rna_metrics.columns.str.lower()
print(df_rna_metrics)

Expand All @@ -254,8 +264,8 @@ def main():
dfs = [df1, df_star, df_mapped, df_rna_metrics]

def rename_sample_df(df: pd.DataFrame):
df['sample'] = df['sample'].astype(str)
df['sample'] = df['sample'].apply(lambda x: re.sub(r"(_R[1,2])$", "", x))
df["sample"] = df["sample"].astype(str)
df["sample"] = df["sample"].apply(lambda x: re.sub(r"(_R[1,2])$", "", x))
return df

new_dfs = map(lambda x: rename_sample_df(x), dfs)
Expand Down
2 changes: 1 addition & 1 deletion wdl/multiqc/multiqc_postalign.wdl
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@ version 1.0
task multiQC_postalign {
input {
Array[File] fastQCReport
File trim_report
File? trim_report
File rsem_report
File star_report
File fc_report
Expand Down
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