Sync dev to master, preparing for release 0.12.0-alpha.0

example/run_pandora.sh

@@ -55,20 +55,20 @@ ${make_prg_executable} from_msa --threads 1 --input msas/ --output-prefix out/pr
 echo "Running ${pandora_executable} index"
 "${pandora_executable}" index --threads 1 out/prgs/pangenome.prg.fa
 echo "Running ${pandora_executable} map"
-"${pandora_executable}" map --threads 1 --genotype -o out/map_toy_sample_1 --genome-size 700 --min-abs-gene-coverage 0 --min-rel-gene-coverage 0 --max-rel-gene-coverage 1000 out/prgs/pangenome.prg.fa.panidx.zip reads/toy_sample_1/toy_sample_1.100x.random.illumina.fastq
+"${pandora_executable}" map --threads 1 --genotype -o out/map_toy_sample_1 --no-gene-coverage-filtering out/prgs/pangenome.prg.fa.panidx.zip reads/toy_sample_1/toy_sample_1.100x.random.illumina.fastq
 echo "Running ${pandora_executable} compare"
-"${pandora_executable}" compare --threads 1 --genotype -o out/output_toy_example_no_denovo --genome-size 700 --min-abs-gene-coverage 0 --min-rel-gene-coverage 0 --max-rel-gene-coverage 1000 out/prgs/pangenome.prg.fa.panidx.zip reads/read_index.tsv
+"${pandora_executable}" compare --threads 1 --genotype -o out/output_toy_example_no_denovo --no-gene-coverage-filtering out/prgs/pangenome.prg.fa.panidx.zip reads/read_index.tsv
 echo "Running pandora without denovo - done!"
 
 echo "Running pandora with denovo..."
 echo "Running ${pandora_executable} discover"
-"${pandora_executable}" discover --threads 1 --outdir out/pandora_discover_out --genome-size 700 --min-abs-gene-coverage 0 --min-rel-gene-coverage 0 --max-rel-gene-coverage 1000 out/prgs/pangenome.prg.fa.panidx.zip reads/read_index.tsv
+"${pandora_executable}" discover --threads 1 --outdir out/pandora_discover_out --no-gene-coverage-filtering out/prgs/pangenome.prg.fa.panidx.zip reads/read_index.tsv
 echo "Running ${make_prg_executable} update"
 ${make_prg_executable} update --threads 1 --update-DS out/prgs/pangenome.update_DS.zip --denovo-paths out/pandora_discover_out/denovo_paths.txt --output-prefix out/updated_prgs/pangenome_updated
 echo "Running ${pandora_executable} index on updated PRGs"
 "${pandora_executable}" index --threads 1 out/updated_prgs/pangenome_updated.prg.fa
 echo "Running ${pandora_executable} compare"
-"${pandora_executable}" compare --threads 1 --genotype -o out/output_toy_example_with_denovo --genome-size 700 --min-abs-gene-coverage 0 --min-rel-gene-coverage 0 --max-rel-gene-coverage 1000 out/updated_prgs/pangenome_updated.prg.fa.panidx.zip reads/read_index.tsv
+"${pandora_executable}" compare --threads 1 --genotype -o out/output_toy_example_with_denovo --no-gene-coverage-filtering out/updated_prgs/pangenome_updated.prg.fa.panidx.zip reads/read_index.tsv
 echo "Running pandora with denovo - done!"
 
 # first compare non-zip files

include/cluster_files.h

@@ -21,7 +21,11 @@ class ClusterFilterFile : public GenericFile {
 public:
     ClusterFilterFile(const fs::path &filepath, bool is_fake_file = false)
         : GenericFile(filepath, is_fake_file){
-        (*this) << "read\tprg\tcluster_size\tstatus\n";
+        (*this) << "read\tprg\tnb_of_unique_minimisers\ttarget_cov\tread_start\t"
+                   "read_end\toverlap\tstatus\tfavoured_cluster_prg\t"
+                   "favoured_cluster_nb_of_unique_minimisers\t"
+                   "favoured_cluster_target_cov\tfavoured_cluster_read_start\t"
+                   "favoured_cluster_read_end\n";
     }
 };
 

include/compare_main.h

@@ -38,11 +38,15 @@ struct CompareOptions {
     uint32_t rng_seed { 0 };
     uint32_t genome_size { 5000000 };
     uint32_t max_diff { 250 };
+    float conflicting_clusters_overlap_threshold { 0.8 };
+    float conflicting_clusters_minimiser_tolerance { 0.05 };
     bool output_vcf { false };
     bool illumina { false };
     float min_absolute_gene_coverage { 3.0 };
     float min_relative_gene_coverage { 0.05 };
     float max_relative_gene_coverage { 100 };
+    float min_gene_coverage_proportion { 0.8 };
+    bool no_gene_coverage_filtering { false };
     bool binomial { false };
     bool do_not_auto_update_params { false };
     uint32_t max_covg { 300 };
@@ -56,6 +60,7 @@ struct CompareOptions {
     float min_allele_fraction_covg_gt { 0 };
     float genotyping_error_rate { 0.01 };
     uint16_t confidence_threshold { 1 };
+    float partial_matching_lower_bound { 0.5 };
     bool keep_extra_debugging_files { false };
 };
 

include/denovo_discovery/discover_main.h

@@ -25,16 +25,21 @@ struct DiscoverOptions {
     uint32_t rng_seed { 0 };
     uint32_t genome_size { 5000000 };
     uint32_t max_diff { 250 };
+    float conflicting_clusters_overlap_threshold { 0.8 };
+    float conflicting_clusters_minimiser_tolerance { 0.05 };
     bool output_kg { false };
     bool illumina { false };
     bool binomial { false };
     bool do_not_auto_update_params { false };
     uint32_t max_covg { 600 };
     float min_absolute_gene_coverage { 3.0 };
     float min_relative_gene_coverage { 0.05 };
-    float max_relative_gene_coverage { 10 };
+    float max_relative_gene_coverage { 100 };
+    float min_gene_coverage_proportion { 0.8 };
+    bool no_gene_coverage_filtering { false };
     uint32_t min_cluster_size { 10 };
     uint32_t max_num_kmers_to_avg { 100 };
+    float partial_matching_lower_bound { 0.5 };
     bool keep_extra_debugging_files { false };
 };
 

include/index.h

@@ -213,7 +213,7 @@ class Index {
         return prg_lengths[id];
     }
 
-    inline const std::vector<uint32_t> & get_prg_max_path_lengths() const {
+    inline std::vector<uint32_t> & get_prg_max_path_lengths() {
         return prg_max_path_lengths;
     }
     inline uint32_t get_prg_max_path_lengths_given_id(size_t id) const {

include/localPRG.h

@@ -157,7 +157,7 @@ class LocalPRG {
         std::vector<LocalNodePtr>&, const uint32_t, const bool, const uint32_t,
         const uint32_t& max_num_kmers_to_average, const uint32_t& sample_id,
         float min_absolute_gene_coverage, float min_relative_gene_coverage,
-        float max_relative_gene_coverage) const;
+        float max_relative_gene_coverage, float min_gene_coverage_proportion, bool no_gene_coverage_filtering) const;
     std::vector<LocalNodePtr> get_valid_vcf_reference(const std::string&) const;
 
     void add_variants_to_vcf(VCF&, pangenome::NodePtr, const std::string&,

include/map_main.h

@@ -38,6 +38,8 @@ struct MapOptions {
     uint32_t rng_seed { 0 };
     uint32_t genome_size { 5000000 };
     uint32_t max_diff { 250 };
+    float conflicting_clusters_overlap_threshold { 0.8 };
+    float conflicting_clusters_minimiser_tolerance { 0.05 };
     bool output_kg { false };
     bool output_vcf { false };
     bool illumina { false };
@@ -47,6 +49,8 @@ struct MapOptions {
     float min_absolute_gene_coverage { 3.0 };
     float min_relative_gene_coverage { 0.05 };
     float max_relative_gene_coverage { 100 };
+    float min_gene_coverage_proportion { 0.8 };
+    bool no_gene_coverage_filtering { false };
     bool genotype { false };
     bool local_genotype { false };
     bool snps_only { false };
@@ -58,6 +62,7 @@ struct MapOptions {
     float min_allele_fraction_covg_gt { 0 };
     float genotyping_error_rate { 0.01 };
     uint16_t confidence_threshold { 1 };
+    float partial_matching_lower_bound { 0.5 };
     bool keep_extra_debugging_files { false };
 };
 

include/minihits.h

@@ -25,9 +25,11 @@ struct pEq {
 class MinimizerHits {
 private:
     std::set<MinimizerHitPtr, pComp> hits;
-
+    uint32_t number_of_equal_read_minimizers;
+    std::vector<uint32_t> *prg_max_path_lengths;  // required to calculate target coverage
 public:
-    MinimizerHits() = default;
+    MinimizerHits(std::vector<uint32_t> *prg_max_path_lengths) :
+        hits(), number_of_equal_read_minimizers(0), prg_max_path_lengths(prg_max_path_lengths) {};
     ~MinimizerHits() = default;
 
     // copy constructors
@@ -38,7 +40,7 @@ class MinimizerHits {
     MinimizerHits(MinimizerHits&& other) = default;
     MinimizerHits& operator=(MinimizerHits&& other) = default;
 
-    inline void insert(const MinimizerHitPtr minimizer_hit) {
+    inline void insert(const MinimizerHitPtr &minimizer_hit) {
         hits.insert(minimizer_hit);
     }
 
@@ -64,14 +66,59 @@ class MinimizerHits {
         return hits.begin();
     }
 
+    inline auto rbegin () const {
+        return hits.rbegin();
+    }
+
+    inline const MinimizerHitPtr& front() const {
+        return *hits.begin();
+    }
+
     inline auto end () const {
         return hits.end();
     }
 
-    inline void clear() { hits.clear(); }
+    inline auto rend () const {
+        return hits.rend();
+    }
+
+    inline const MinimizerHitPtr& back() const {
+        return *hits.rbegin();
+    }
+
+    uint32_t read_span_size() const;
+
+    inline void clear() {
+        hits.clear();
+        number_of_equal_read_minimizers=0;
+    }
+
+    inline void increment_number_of_equal_read_minimizers() {
+        number_of_equal_read_minimizers++;
+    }
+
+    inline uint32_t get_number_of_equal_read_minimizers() const {
+        return number_of_equal_read_minimizers;
+    }
+
+    inline size_t get_number_of_unique_mini_in_cluster() const {
+        return size() - number_of_equal_read_minimizers;
+    }
 
     bool operator<(const MinimizerHits &rhs) const;
 
     std::pair<uint32_t, uint32_t> get_strand_counts() const;
+
+    /**
+     * Returns a proportion denoting the amount of overlap between this cluster and the
+     * cluster passed as an argument. The proportion is over the smallest cluster.
+     */
+    double overlap_amount(const MinimizerHits& cluster) const;
+
+    double target_coverage() const;
+
+    bool is_preferred_to(const MinimizerHits& cluster,
+        double minimisers_tolerance) const;
+
 };
 #endif

include/utils.h

@@ -70,8 +70,8 @@ void define_clusters(
     const std::string &sample_name,
     const Seq &seq,
     MinimizerHitClusters& clusters_of_hits,
-    const std::vector<uint32_t> &prg_min_path_lengths,
-    const std::vector<std::string> &prg_names,
+    const std::vector<uint32_t> &prg_max_path_lengths,
+    std::vector<std::string> &prg_names,
     std::shared_ptr<MinimizerHits> &minimizer_hits, const int max_diff,
     const float& fraction_kmers_required_for_cluster, const uint32_t min_cluster_size,
     const uint32_t expected_number_kmers_in_read_sketch,
@@ -83,6 +83,8 @@ MinimizerHitClusters filter_clusters(
     const MinimizerHitClusters& clusters_of_hits,
     const std::vector<std::string> &prg_names,
     ClusterFilterFile& cluster_filter_file,
+    const float overlap_threshold,
+    const float conflicting_clusters_minimiser_tolerance,
     const uint32_t rng_seed = 0
 );
 
@@ -94,7 +96,7 @@ void add_clusters_to_pangraph(
 MinimizerHitClusters get_minimizer_hit_clusters(
     const std::string &sample_name,
     const Seq &seq,
-    const std::vector<uint32_t> &prg_min_path_lengths,
+    std::vector<uint32_t> &prg_max_path_lengths,
     const std::vector<std::string> &prg_names,
     std::shared_ptr<MinimizerHits> &minimizer_hits,
     const int max_diff,
@@ -110,8 +112,10 @@ uint32_t pangraph_from_read_file(const SampleData& sample,
     const int max_diff, const float& e_rate,
     const fs::path& sample_outdir, const uint32_t min_cluster_size = 10,
     const uint32_t genome_size = 5000000, const uint32_t max_covg = 300,
+    const float conflicting_clusters_overlap_threshold=0.8,
+    const float conflicting_clusters_minimiser_tolerance=0.05,
     uint32_t threads = 1, const bool keep_extra_debugging_files = false,
-    const uint32_t rng_seed = 0);
+    const uint32_t rng_seed = 0, const float partial_matching_lower_bound=0.5);
 
 void infer_most_likely_prg_path_for_pannode(
     const std::vector<std::shared_ptr<LocalPRG>>&, PanNode*, uint32_t, float);

src/compare_main.cpp

@@ -69,6 +69,16 @@ void setup_compare_subcommand(CLI::App& app)
         ->type_name("INT")
         ->group("Mapping");
 
+    description
+        = "When two clusters of hits are conflicting, the one with highest number of unique minimisers "
+          "will be kept. However, if the difference between the number of unique minimisers is too small, "
+          "less than this parameter, then we will prefer the cluster that has higher target coverage.";
+    compare_subcmd
+        ->add_option("--cluster-mini-tolerance", opt->conflicting_clusters_minimiser_tolerance, description)
+        ->capture_default_str()
+        ->type_name("FLOAT")
+        ->group("Mapping");
+
     compare_subcmd
         ->add_flag("--loci-vcf", opt->output_vcf, "Save a VCF file for each found loci")
         ->group("Input/Output");
@@ -140,6 +150,26 @@ void setup_compare_subcommand(CLI::App& app)
         ->type_name("FLOAT")
         ->group("Filtering");
 
+    compare_subcmd
+        ->add_option(
+            "--min-gene-coverage-proportion", opt->min_gene_coverage_proportion,
+            "Minimum gene coverage proportion to keep a gene. "
+            "Given the coverage on the kmers of the maximum likelihood path of a gene, we compute "
+            "the number of bases that have at least one read covering it. "
+            "If the proportion of such bases is larger than the value in this "
+            "parameter, the gene is kept. Otherwise, the gene is filtered out.")
+        ->capture_default_str()
+        ->type_name("FLOAT")
+        ->group("Filtering");
+
+    compare_subcmd
+        ->add_flag(
+            "--no-gene-coverage-filtering", opt->no_gene_coverage_filtering,
+            "Do not filter genes based on their coverage, effectively ignoring params "
+            "--min-abs-gene-coverage, --min-rel-gene-coverage, --max-rel-gene-coverage and --min-gene-coverage-proportion. "
+            "This is useful if you are not using read datasets.")
+        ->group("Filtering");
+
     description = "Add extra step to carefully genotype sites.";
     auto* gt_opt = compare_subcmd->add_flag("--genotype", opt->genotype, description)
                        ->group("Consensus/Variant Calling");
@@ -159,6 +189,26 @@ void setup_compare_subcommand(CLI::App& app)
         ->type_name("INT")
         ->group("Mapping");
 
+    description
+        = "Minimum proportion of overlap between two clusters of hits to consider "
+          "them conflicting. Only one of the conflicting clusters will be kept.";
+    compare_subcmd
+        ->add_option("--min-cluster-overlap", opt->conflicting_clusters_overlap_threshold, description)
+        ->capture_default_str()
+        ->type_name("FLOAT")
+        ->group("Mapping");
+
+    description
+        = "Allows for partial matching between reads and a PRG. If this value is for e.g. 0.5, it means that "
+          "pandora will match a read to a PRG if the cluster of hits has size at least 0.5 * expected cluster size "
+          "for the given error rate and kmer value. Lower values allow for more hits, but possibly for false positive "
+          "matches.";
+    compare_subcmd
+        ->add_option("--partial-matching-lower-bound", opt->partial_matching_lower_bound, description)
+        ->capture_default_str()
+        ->type_name("FLOAT")
+        ->group("Mapping");
+
     description = "Maximum number of kmers to average over when selecting the maximum "
                   "likelihood path";
     compare_subcmd->add_option("--kmer-avg", opt->max_num_kmers_to_avg, description)
@@ -285,8 +335,10 @@ int pandora_compare(CompareOptions& opt)
                                 << sample_fpath << " (this will take a while)";
         uint32_t covg = pangraph_from_read_file(sample, pangraph_sample, index,
             opt.max_diff, opt.error_rate, sample_outdir,
-            opt.min_cluster_size, opt.genome_size, opt.max_covg, opt.threads,
-            opt.keep_extra_debugging_files, opt.rng_seed);
+            opt.min_cluster_size, opt.genome_size, opt.max_covg,
+            opt.conflicting_clusters_overlap_threshold, opt.conflicting_clusters_minimiser_tolerance,
+            opt.threads, opt.keep_extra_debugging_files, opt.rng_seed,
+            opt.partial_matching_lower_bound);
 
         if (pangraph_sample->nodes.empty()) {
             BOOST_LOG_TRIVIAL(warning)
@@ -315,7 +367,8 @@ int pandora_compare(CompareOptions& opt)
             local_prg->add_consensus_path_to_fastaq(consensus_fq, c->second, kmp, lmp,
                 index.get_window_size(), opt.binomial, covg, opt.max_num_kmers_to_avg, 0,
                 opt.min_absolute_gene_coverage, opt.min_relative_gene_coverage,
-                opt.max_relative_gene_coverage);
+                opt.max_relative_gene_coverage, opt.min_gene_coverage_proportion,
+                opt.no_gene_coverage_filtering);
 
             if (kmp.empty()) {
                 c = pangraph_sample->remove_node(c->second);