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add assigning points based on sensitivity
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@donaldcampbelljr
donaldcampbelljr committed Sep 6, 2024
1 parent 8a0ce95 commit d1796c8
Showing 1 changed file with 101 additions and 71 deletions.
172 changes: 101 additions & 71 deletions bedboss/refgenome_validator/refgenomevalidator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -249,10 +249,10 @@ def process_compat_stats(self, compat_stats: dict, genome_alias: str) -> dict:
Tiers Definition ----
Tier1: Excellent compatibility
Tier2: Good compatibility, may need some processing
Tier3: Bed file needs processing to work (shifted hg38 to hg19?)
Tier4: Poor compatibility
Tier1: Excellent compatibility, 0 pts
Tier2: Good compatibility, may need some processing, 1-3 pts
Tier3: Bed file needs processing to work (shifted hg38 to hg19?), 3-6 pts
Tier4: Poor compatibility, 7-9 pts
:param dict compat_stats: dicitionary containing unprocessed compat stats
:param str genome_alias:
Expand All @@ -267,73 +267,103 @@ def process_compat_stats(self, compat_stats: dict, genome_alias: str) -> dict:

# Currently will proceed with discrete buckets, however, we could do a point system in the future
final_compat_rating = "Tier 1"

if not compat_stats["chrom_name_stats"]["passed_chrom_names"]:
# if the file did not pass the first layer, immediately bump it down a Tier
# this pass_chrom_names bool is determined via if q_and_not_m > 1

final_compat_rating = "Tier 2"
# Ok, there were some chroms in the bed file NOT in the chromsizes file
# How many? If it's a lot, we should penalize and knock it down the tier list
# use jaccard index to determine this

if compat_stats["chrom_name_stats"]["jaccard_index"] >= 0.90:
# Keep at current tier
pass
elif compat_stats["chrom_name_stats"]["jaccard_index"] >= 0.60:
final_compat_rating = "Tier 3"
elif compat_stats["chrom_name_stats"]["jaccard_index"] < 0.60:
final_compat_rating = "Tier 4"
else:
# if the bed file has passed the first layer, we should check the chrom lengths
# careful using jaccard index here for comparison as you could have a small bed file with one chr
# that is in both the ref and query but would still have a low jaccard index
if not compat_stats["chrom_length_stats"]["beyond_range"] == 0:
final_compat_rating = "Tier 2"
# Some chroms are beyond range. Determine how this should affect tier rating.
# We can assess what percentage of the chroms in bed file extended beyond the chromsizes file
# and also compare to how many extended chroms are in the genome.
if (
compat_stats["chrom_length_stats"]["percentage_bed_chrm_beyond"]
>= 0.50
):
if (
compat_stats["chrom_length_stats"][
"percentage_genome_chrm_beyond"
]
>= 0.50
):
final_compat_rating = "Tier 4"
if (
compat_stats["chrom_length_stats"][
"percentage_genome_chrm_beyond"
]
< 0.50
):
final_compat_rating = "Tier 3"
if (
compat_stats["chrom_length_stats"]["percentage_bed_chrm_beyond"]
<= 0.50
):
if (
compat_stats["chrom_length_stats"][
"percentage_genome_chrm_beyond"
]
>= 0.30
):
final_compat_rating = "Tier 4"
if (
compat_stats["chrom_length_stats"][
"percentage_genome_chrm_beyond"
]
< 0.30
):
final_compat_rating = "Tier 3"

else:
# Keep at Tier 1 and run analysis igd_stats for layer 3 analysis
if compat_stats["igd_stats"] and compat_stats["igd_stats"] != {}:
self.process_igd_stats(compat_stats["igd_stats"])
points_rating = 0 # we will add points increasing the level and then sort into various tiers at the end

# Check extra sequences sensitivity and assign points based on how sensitive the outcome is
# sensitivity = 1 is considered great and no points should be assigned
if compat_stats["chrom_name_stats"]["XS"] < 1:
points_rating += 3
if compat_stats["chrom_name_stats"]["XS"] < 0.7:
points_rating += 1
if compat_stats["chrom_name_stats"]["XS"] < 0.5:
points_rating += 1
if compat_stats["chrom_name_stats"]["XS"] < 0.3:
points_rating += 1

# Check OOBR and assign points based on sensitivity
if compat_stats["chrom_name_stats"]["OOBR"] < 1:
points_rating += 3
if compat_stats["chrom_name_stats"]["OOBR"] < 0.7:
points_rating += 1
if compat_stats["chrom_name_stats"]["OOBR"] < 0.5:
points_rating += 1
if compat_stats["chrom_name_stats"]["OOBR"] < 0.3:
points_rating += 1

# Check Sequence Fit - comparing lengths in queries vs lengths of queries in ref genome vs not in ref genome
# TODO

# if not compat_stats["chrom_name_stats"]["passed_chrom_names"]:
# # if the file did not pass the first layer, immediately bump it down a Tier
# # this pass_chrom_names bool is determined via if q_and_not_m > 1
#
# final_compat_rating = "Tier 2"
# # Ok, there were some chroms in the bed file NOT in the chromsizes file
# # How many? If it's a lot, we should penalize and knock it down the tier list
# # use jaccard index to determine this
#
# if compat_stats["chrom_name_stats"]["jaccard_index"] >= 0.90:
# # Keep at current tier
# pass
# elif compat_stats["chrom_name_stats"]["jaccard_index"] >= 0.60:
# final_compat_rating = "Tier 3"
# elif compat_stats["chrom_name_stats"]["jaccard_index"] < 0.60:
# final_compat_rating = "Tier 4"
# else:
# # if the bed file has passed the first layer, we should check the chrom lengths
# # careful using jaccard index here for comparison as you could have a small bed file with one chr
# # that is in both the ref and query but would still have a low jaccard index
# if not compat_stats["chrom_length_stats"]["beyond_range"] == 0:
# final_compat_rating = "Tier 2"
# # Some chroms are beyond range. Determine how this should affect tier rating.
# # We can assess what percentage of the chroms in bed file extended beyond the chromsizes file
# # and also compare to how many extended chroms are in the genome.
# if (
# compat_stats["chrom_length_stats"]["percentage_bed_chrm_beyond"]
# >= 0.50
# ):
# if (
# compat_stats["chrom_length_stats"][
# "percentage_genome_chrm_beyond"
# ]
# >= 0.50
# ):
# final_compat_rating = "Tier 4"
# if (
# compat_stats["chrom_length_stats"][
# "percentage_genome_chrm_beyond"
# ]
# < 0.50
# ):
# final_compat_rating = "Tier 3"
# if (
# compat_stats["chrom_length_stats"]["percentage_bed_chrm_beyond"]
# <= 0.50
# ):
# if (
# compat_stats["chrom_length_stats"][
# "percentage_genome_chrm_beyond"
# ]
# >= 0.30
# ):
# final_compat_rating = "Tier 4"
# if (
# compat_stats["chrom_length_stats"][
# "percentage_genome_chrm_beyond"
# ]
# < 0.30
# ):
# final_compat_rating = "Tier 3"
#
# else:
# # Keep at Tier 1 and run analysis igd_stats for layer 3 analysis
# if compat_stats["igd_stats"] and compat_stats["igd_stats"] != {}:
# self.process_igd_stats(compat_stats["igd_stats"])

# Run analysis igd_stats for layer 3 analysis
# WIP, currently only showing IGD stats for informational purposes
if compat_stats["igd_stats"] and compat_stats["igd_stats"] != {}:
self.process_igd_stats(compat_stats["igd_stats"])

processed_stats[genome_alias].update({"Compatibility": final_compat_rating})

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