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Add query to ref coord mapping #120

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Add query to ref coord mapping #120

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5b55e6b
add query to ref coord mapping
chilampoon Oct 10, 2023
3c807bb
rm redundant interpolation
chilampoon Oct 11, 2023
804fb9b
change N ref ops to false
chilampoon Oct 12, 2023
a62f46d
intron aware extract_ref_reg
chilampoon Oct 15, 2023
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add query to ref coord mapping
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@chilampoon
chilampoon committed Oct 10, 2023
commit 5b55e6b4efc96d5392fb494409af5571d9bd4db5
28 changes: 26 additions & 2 deletions src/remora/data_chunks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@
)
QUERY_OPS = np.array([True, True, False, False, True, False, False, True, True])
REF_OPS = np.array([True, False, True, True, False, False, False, True, True])
REFCOORD_OPS = np.array([True, False, True, False, False, False, False, True, True])
CIGAR_CODES = ["M", "I", "D", "N", "S", "H", "P", "=", "X"]
CODE_TO_OP = {
"M": 0,
Expand Down Expand Up @@ -59,10 +60,16 @@ def map_ref_to_signal(*, query_to_signal, ref_to_query_knots):
query_to_signal (np.array): Query to signal coordinate mapping
ref_to_query_knots (np.array): Reference to query coordinate mapping
"""
query_to_ref_coords = np.interp(
np.arange(query_to_signal.size),
np.arange(ref_to_query_knots.size),
ref_to_query_knots
).astype(int)

return np.floor(
np.interp(
ref_to_query_knots,
np.arange(query_to_signal.size),
query_to_ref_coords,
query_to_signal,
)
).astype(int)
Expand Down Expand Up @@ -98,11 +105,28 @@ def make_sequence_coordinate_mapping(cigar):
query_knots = np.concatenate(
[[0], (query_knots[is_match] - offsets).T.flatten(), [query_knots[-1]]]
)
knots = np.interp(np.arange(ref_knots[-1] + 1), ref_knots, query_knots)
ref_coords = get_ref_coords(ops, lens)
knots = np.interp(np.concatenate([[0], ref_coords]), ref_knots, query_knots)

return knots


def get_ref_coords(ops, lens):
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The dumb version of this function is:

def get_ref_coords(ops, lens):
    ref_coords = []
    s = 1

    for op, l in zip(ops, lens):
        if op in [3]:
            s += l
        elif op in [1,4,5]:
            continue
        elif op in [0,2,7,8]:
            # mapped
            pos_list = list(range(s, s + l))
            ref_coords.extend(pos_list)
            s += l
        
    return ref_coords

'''
Map query base to reference coordinates (1-based).
Returns
array shape (ref_len+1,); ref_len = len(aln.get_reference_sequences())
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'''
starts = np.cumsum(np.where(REF_OPS[ops], lens, 0)) - np.where(REF_OPS[ops], lens, 0)
ranges = [
np.arange(start, start + l)
for op, start, l in zip(ops, starts, lens)
if REFCOORD_OPS[op]
]
ref_coords = np.concatenate(ranges) + 1
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@marcus1487 marcus1487 Oct 11, 2023 •
edited
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I still feel like there is extra logic here. I think the fix here might be as simple as completely dropping the skip cigar ops. Do you get the same results if you switch the REF_OPS skip code value to False without any other code changes?

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I was thinking about the same thing I think you're right - just changing the intron operation to False in REF_OPS can work as well... got the same results for genomic reads and didn't raise errors for transcriptomic reads

return ref_coords


def compute_ref_to_signal(query_to_signal, cigar):
ref_to_read_knots = make_sequence_coordinate_mapping(cigar)
assert query_to_signal.size == ref_to_read_knots[-1].astype(int) + 1, (
Expand Down