Seqwho

CHANGELOG.md

@@ -516,6 +516,8 @@ for more information.
   - Mark duplicate reads from PacBio sequencing of an amplified library
 - [**WhatsHap**](https://whatshap.readthedocs.io)
   - WhatsHap is a software for phasing genomic variants using DNA sequencing reads
+- [**SeqWho**](https://daehwankimlab.github.io/seqwho/)
+  - Tool to determine a FASTQ(A) sequencing file identity, both source protocol and species of origin.
 
 ### Module feature additions
 

docs/modules/seqwho.md

@@ -0,0 +1,11 @@
+---
+name: SeqWho
+url: https://daehwankimlab.github.io/seqwho/
+description: >
+  SeqWho is a reliable and extremely rapid program designed to determine a FASTQ(A) sequencing file identity, both source protocol and species of origin.
+---
+
+The SeqWho module parses results generated by
+[SeqWho](https://daehwankimlab.github.io/seqwho/),
+a tool that allows you to determine a FASTQ(A) sequencing file identity, both source protocol and species of origin so you can see if the composition of
+the library matches with what you expect.

multiqc/modules/seqwho/__init__.py

@@ -0,0 +1,3 @@
+from .seqwho import MultiqcModule
+
+__all__ = ["MultiqcModule"]

multiqc/modules/seqwho/seqwho.py

@@ -0,0 +1,266 @@
+""" MultiQC module to parse output from SeqWho """
+
+import json
+import logging
+from collections import OrderedDict
+
+from multiqc import config
+from multiqc.modules.base_module import BaseMultiqcModule, ModuleNoSamplesFound
+from multiqc.plots import linegraph, bargraph
+from multiqc.utils import mqc_colour
+
+# Initialise the logger
+log = logging.getLogger(__name__)
+
+
+LIBRARIES = ["amplicon", "bisulf", "wxs", "chip", "wgs", "dnase", "rnaseq", "atac", "mirnaseq"]
+SPECIES = ["human", "mouse"]
+
+
+class MultiqcModule(BaseMultiqcModule):
+    """SeqWho module"""
+
+    def __init__(self):
+        # Initialise the parent object
+        super(MultiqcModule, self).__init__(
+            name="SeqWho",
+            anchor="seqwho",
+            href="https://daehwankimlab.github.io/seqwho/",
+            info="is a tool to determine a FASTQ(A) sequencing file identity, both source protocol and species of origin.",
+            # doi=""
+        )
+
+        # Find and load any SeqWho reports
+        self.seqwho_data = dict()
+        self.seqwho_qualdis = dict()
+        self.seqwho_qualscore = dict()
+        self.seqwho_readdist = dict()
+
+        for f in self.find_log_files("seqwho", filehandles=True):
+            self.parse_json(f)
+
+        # Superfluous function call to confirm that it is used in this module
+        # Replace None with actual version if it is available
+        self.add_software_version(None)
+
+        # Filter to strip out ignored sample names
+        self.seqwho_data = self.ignore_samples(self.seqwho_data)
+        self.seqwho_qualdis = self.ignore_samples(self.seqwho_qualdis)
+        self.seqwho_qualscore = self.ignore_samples(self.seqwho_qualscore)
+        self.seqwho_readdist = self.ignore_samples(self.seqwho_readdist)
+
+        if len(self.seqwho_data) == 0:
+            raise ModuleNoSamplesFound
+
+        log.info(f"Found {len(self.seqwho_data)} reports")
+
+        # Write parsed report data to a file
+        self.write_data_file(self.seqwho_data, "multiqc_seqwho")
+
+        # General Stats Table
+        self.seqwho_general_stats_table()
+
+        # SeqWho MLE Species Table
+        self.seqwho_species_plot()
+
+        # SeqWho MLE Sequencing Table
+        self.seqwho_library_plot()
+
+        # Quality Distribution
+        self.seqwho_qualdist_plot()
+
+        # Quality Score
+        self.seqwho_qualscore_plot()
+
+        # Read Distribution
+        self.seqwho_readdist_plot()
+
+    # Parse our nice little JSON file
+    def parse_json(self, f):
+        """Parse the JSON output from SeqWho and save the summary statistics"""
+        try:
+            parsed_json = json.load(f["f"])
+        except json.JSONDecodeError:
+            log.warning(f"Could not parse SeqWho JSON: '{f['fn']}'")
+            return
+
+        # Get sample name from JSON first
+        for s_name, data in parsed_json.items():
+            s_name = self.clean_s_name(s_name, f["root"])
+            self.add_data_source(f, s_name)
+            self.seqwho_data[s_name] = {}
+
+            call_data = data["Call"]
+            self.seqwho_data[s_name]["predicted_species"] = call_data["Species"]
+            self.seqwho_data[s_name]["predicted_library"] = call_data["Library"]
+            self.seqwho_data[s_name]["mle"] = call_data["Maximum Likelihood Estimate"]
+            self.seqwho_data[s_name]["est_read_number"] = data["Estimated Read Number"]
+
+            # Make MLE Matrix table for subset of predicted species and library
+            mle_matrix = call_data["MLE Matrix"]
+            mle_columns = SPECIES + LIBRARIES
+            for i in mle_columns:
+                self.seqwho_data[s_name][i] = mle_matrix[i]
+
+            # Make a Quality Score vs count  version of the data
+            self.seqwho_qualdis[s_name] = OrderedDict()
+            qual_dist = data["Quality Dist"]
+            for i in range(len(qual_dist)):
+                self.seqwho_qualdis[s_name][i] = qual_dist[i]
+
+            # Make a Quality score vs position  version of the data
+            self.seqwho_qualscore[s_name] = OrderedDict()
+            qual_scores = data["Quality Scores"]
+            for i in range(len(qual_scores)):
+                self.seqwho_qualscore[s_name][i] = qual_scores[i]
+
+            # Make a Read Length vs count of the data
+            self.seqwho_readdist[s_name] = OrderedDict()
+            read_dist = data["Read lengths"]
+            for i in range(len(read_dist)):
+                self.seqwho_readdist[s_name][i] = read_dist[i]
+
+    def seqwho_general_stats_table(self):
+        """Take the parsed stats from the SeqWho report and add it to the
+        General Statistics table at the top of the report"""
+        species_scale = mqc_colour.mqc_colour_scale("Dark2")
+        species_colors = [{v: species_scale.get_colour(i, lighten=0.5)} for i, v in enumerate(SPECIES)]
+        library_scale = mqc_colour.mqc_colour_scale("Accent")
+        library_colors = [{v: library_scale.get_colour(i, lighten=0.5)} for i, v in enumerate(LIBRARIES)]
+
+        headers = {
+            "predicted_species": {
+                "title": "Pred Species",
+                "description": "Predicted species",
+                "cond_formatting_colours": species_colors,
+                "cond_formatting_rules": {v: [{"s_eq": v}] for v in SPECIES},
+                "scale": False,
+            },
+            "predicted_library": {
+                "title": "Pred Library",
+                "description": "Predicted library type",
+                "cond_formatting_colours": library_colors,
+                "cond_formatting_rules": {v: [{"s_eq": v}] for v in LIBRARIES},
+                "scale": False,
+            },
+            "mle": {
+                "title": "Max Likelihood Est",
+                "description": "Overall maximum likelihood estimate (overall)",
+                "min": 0,
+                "format": "{:,.3f}",
+                "scale": "RdYlGn",
+            },
+            "est_read_number": {
+                "title": f"{config.read_count_prefix} Est Reads",
+                "description": f"Estimated read number ({config.read_count_desc})",
+                "min": 0,
+                "modify": lambda x: x * config.read_count_multiplier,
+                "scale": "Blues",
+                "shared_key": "read_count",
+            },
+        }
+        self.general_stats_addcols(self.seqwho_data, headers)
+
+    def seqwho_species_plot(self):
+        """
+        Take the Maximum Likelihood Species data from the SeqWho report and make
+        barchart
+        """
+
+        config = {
+            "id": "seqwho_species_plot",
+            "title": "SeqWho: Species",
+            "ylab": "Maximum likelihood estimate",
+            "ymax": 1.0,
+            "stacking": None,
+            "cpswitch": False,
+            "cpswitch_counts_label": "Maximum likelihood",
+            "tt_decimals": 3,
+        }
+
+        self.add_section(
+            name="Species",
+            anchor="seqwho_species",
+            description="This plot shows the maximum likelihood that a given species matches.",
+            plot=bargraph.plot(self.seqwho_data, SPECIES, config),
+        )
+
+    def seqwho_library_plot(self):
+        """Take the Maximum Likelihood Library data from the SeqWho report and make a
+        barplot"""
+
+        # Config for the plot
+        config = {
+            "id": "seqwho_sequencing_plot",
+            "title": "SeqWho: Library Type",
+            "ylab": "Maximum likelihood estimate",
+            "ymax": 1.0,
+            "stacking": None,
+            "cpswitch": False,
+            "cpswitch_counts_label": "Maximum likelihood",
+            "tt_decimals": 3,
+        }
+
+        self.add_section(
+            name="Library Type",
+            anchor="seqwho_library",
+            description="This plot shows the maximum likelihood that a given library matches.",
+            plot=bargraph.plot(self.seqwho_data, LIBRARIES, config),
+        )
+
+    def seqwho_qualdist_plot(self):
+        """Generate the Average Sequence Quality Distribution plot"""
+        pconfig = {
+            "id": "seqwho_qualdis_plot",
+            "title": "SeqWho: Per Sequence Quality Scores",
+            "ylab": "Reads",
+            "xlab": "Sequence Quality (Phred)",
+            "xDecimals": False,
+            "ymin": 0,
+            "tt_label": "<b>Phred {point.x}</b>: {point.y:.0f} reads",
+        }
+
+        self.add_section(
+            name="Predicted Per Sequence Quality Scores",
+            anchor="seqwho_qualdis",
+            description="This plot shows the predicted number of reads with average quality scores.",
+            plot=linegraph.plot(self.seqwho_qualdis, pconfig),
+        )
+
+    def seqwho_qualscore_plot(self):
+        """Generate the Average Quality Score per position plot"""
+        pconfig = {
+            "id": "seqwho_qualscore_plot",
+            "title": "SeqWho: Quality Score",
+            "ylab": "Sequence Quality (Phred)",
+            "xlab": "Position (bp)",
+            "xDecimals": False,
+            "ymin": 0,
+            "tt_label": "<b>Base {point.x} </b>: {point.y}",
+        }
+
+        self.add_section(
+            name="Predicted Mean Quality Scores",
+            anchor="seqwho_qualscore",
+            description="This plot shows the predicted mean quality value across each base position in the read.",
+            plot=linegraph.plot(self.seqwho_qualscore, pconfig),
+        )
+
+    def seqwho_readdist_plot(self):
+        """Generate the number of reads with certain length plot"""
+        pconfig = {
+            "id": "seqwho_readdist_plot",
+            "title": "SeqWho: Read Distribution",
+            "ylab": "Reads",
+            "xlab": "Length (bp)",
+            "xDecimals": False,
+            "ymin": 0,
+            "tt_label": "<b>Base {point.x} bp</b>: {point.y} reads",
+        }
+
+        self.add_section(
+            name="Predicted Read Distribution",
+            anchor="seqwho_readdist",
+            description="This plot shows predicted the number of reads with certain lengths.",
+            plot=linegraph.plot(self.seqwho_readdist, pconfig),
+        )

multiqc/utils/config_defaults.yaml

@@ -793,6 +793,10 @@ module_order:
       module_tag:
         - RNA
         - DNA
+  - seqwho:
+      module_tag:
+        - RNA
+        - DNA
   - afterqc:
       module_tag:
         - RNA

multiqc/utils/search_patterns.yaml

@@ -767,6 +767,9 @@ samtools/rmdup:
   shared: true
 sargasso:
   fn: "overall_filtering_summary.txt"
+seqwho:
+  contents: '  "Per Base Seq": ['
+  num_lines: 10
 seqyclean:
   fn: "*_SummaryStatistics.tsv"
 sexdeterrmine:

setup.py

@@ -185,6 +185,7 @@
             "samtools = multiqc.modules.samtools:MultiqcModule",
             "sargasso = multiqc.modules.sargasso:MultiqcModule",
             "seqyclean = multiqc.modules.seqyclean:MultiqcModule",
+            "seqwho = multiqc.modules.seqwho:MultiqcModule",
             "sexdeterrmine = multiqc.modules.sexdeterrmine:MultiqcModule",
             "sickle = multiqc.modules.sickle:MultiqcModule",
             "skewer = multiqc.modules.skewer:MultiqcModule",