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1
+ ---
2
+ title: "Binding Scores"
3
+ description: "Schema reference for computed binding score tables"
4
+ ---
5
+
6
+ These are the computed outputs of the data labeling pipeline.
7
+
8
+ ---
9
+
10
+ ## Binding Scores
11
+
12
+ **File:** `binding-scores-YYYYMMDD.parquet`
13
+
14
+ Aggregated binding scores per candidate and antigen pair. Replicate binding scores are averaged across replicates and pivoted so that each antigen concentration becomes its own column.
15
+
16
+ **Grain:** one row per unique `(candidate_id, sino_catalog_id)`.
17
+
18
+ ### Fixed Columns
19
+
20
+ | Column | Type | Description |
21
+ | :--- | :--- | :--- |
22
+ | `candidate_library_id` | `string` | Identifier of the candidate library consumed by this sample. |
23
+ | `candidate_name` | `string` | Customer-provided sequence name. |
24
+ | `candidate_id` | `string` | Blake-3 content digest of the reference sequence. |
25
+ | `candidate_sequence` | `string` | The candidate amino acid sequence. |
26
+ | `variant_id` | `string` | Blake-3 content digest of the variant sequence. |
27
+ | `variant_sequence` | `string` | The variant sequence. |
28
+ | `sino_catalog_id` | `string` | Sino catalog identifier for the antigen used in the binding assay. |
29
+ | `antigen_gene_name` | `string` | Gene name of the antigen. |
30
+ | `antigen_sequence` | `string` | Amino acid sequence of the antigen. |
31
+ | `targeting` | `boolean` | Whether the candidate was designed to target this antigen. |
32
+ | `is_expressed` | `boolean` | Whether the candidate is expressed in at least one sample. |
33
+
34
+ ### Dynamic Concentration Columns
35
+
36
+ <Note>
37
+ In addition to the fixed columns above, this table contains **dynamic columns** for each antigen concentration used in the experiment. The column names follow the pattern `binding_score_{conc}nM` and `binding_score_{conc}nM_std`.
38
+ </Note>
39
+
40
+ For our standard workflow, you will see these additional columns:
41
+
42
+ | Column | Type | Description |
43
+ | :--- | :--- | :--- |
44
+ | `binding_score_5nM` | `float` | Mean log binding score at 5 nM. |
45
+ | `binding_score_5nM_std` | `float` | Standard error of the log binding score at 5 nM. |
46
+ | `binding_score_50nM` | `float` | Mean log binding score at 50 nM. |
47
+ | `binding_score_50nM_std` | `float` | Standard error of the log binding score at 50 nM. |
48
+ | `binding_score_500nM` | `float` | Mean log binding score at 500 nM. |
49
+ | `binding_score_500nM_std` | `float` | Standard error of the log binding score at 500 nM. |
50
+
51
+ ---
52
+
53
+ ## Replicate Binding Scores
54
+
55
+ **File:** `replicate-binding-scores-YYYYMMDD.parquet`
56
+
57
+ Per-replicate binding scores unrolled across antigen concentrations. Each row represents a single candidate measured in a specific expression/binding sample pair at a specific antigen concentration. Use this table to inspect replicate-level variation and per-sample UMI counts.
58
+
59
+ **Grain:** one row per `(candidate_id, binding_sample_id, antigen_concentration_nM)`.
60
+
61
+ | Column | Type | Nullable | Description |
62
+ | :--- | :--- | :--- | :--- |
63
+ | `candidate_library_id` | `string` | no | Identifier of the candidate library consumed by this sample. |
64
+ | `expression_sample_id` | `string` | no | Sample identifier for the expression (base) sample. |
65
+ | `binding_sample_id` | `string` | no | Sample identifier for the binding (dose) sample. |
66
+ | `candidate_name` | `string` | no | Customer-provided sequence name. |
67
+ | `candidate_id` | `string` | no | Blake-3 content digest of the reference sequence. |
68
+ | `candidate_sequence` | `string` | no | The candidate amino acid sequence. |
69
+ | `variant_id` | `string` | no | Blake-3 content digest of the variant sequence. |
70
+ | `variant_sequence` | `string` | no | The variant sequence. |
71
+ | `sino_catalog_id` | `string` | no | Sino catalog identifier for the antigen. |
72
+ | `antigen_gene_name` | `string` | no | Gene name of the antigen. |
73
+ | `antigen_sequence` | `string` | no | Amino acid sequence of the antigen. |
74
+ | `antigen_concentration_nM` | `float` | no | Antigen concentration in nanomolar. |
75
+ | `targeting` | `boolean` | no | Whether the candidate was designed to target this antigen. |
76
+ | `is_expressed` | `boolean` | no | Whether the candidate is expressed. |
77
+ | `binding_score` | `float` | yes | Log binding score. Null when UMI count thresholds are not met. |
78
+ | `expression_umi_count` | `integer` | yes | UMI count from the expression (base) sample. |
79
+ | `binding_umi_count` | `integer` | yes | UMI count from the binding (dose) sample. |
80
+
81
+ **Key relationships:**
82
+ - `expression_sample_id` and `binding_sample_id` both correspond to `dim_samples.sample_id`.
83
+ - `candidate_id` is the shared candidate key across all tables.
84
+ - `variant_id` is the shared variant key across all tables.
85
+
86
+ ## Specificity Scores
87
+
88
+ **File:** `specificity-scores-YYYYMMDD.parquet`
89
+
90
+ Aggregated specificity scores per candidate and antigen pair. Replicate specificity scores are averaged across replicates and pivoted so that each antigen concentration becomes its own column.
91
+
92
+ **Grain:** one row per unique `(candidate_id, sino_catalog_id)`.
93
+
94
+ ### Fixed Columns
95
+
96
+ | Column | Type | Description |
97
+ | :--- | :--- | :--- |
98
+ | `candidate_library_id` | `string` | Identifier of the candidate library consumed by this sample. |
99
+ | `candidate_name` | `string` | Customer-provided sequence name. |
100
+ | `candidate_id` | `string` | Blake-3 content digest of the reference sequence. |
101
+ | `candidate_sequence` | `string` | The candidate amino acid sequence. |
102
+ | `variant_id` | `string` | Blake-3 content digest of the variant sequence. |
103
+ | `variant_sequence` | `string` | The variant sequence. |
104
+ | `sino_catalog_id` | `string` | Sino catalog identifier for the antigen used in the binding assay. |
105
+ | `antigen_gene_name` | `string` | Gene name of the antigen. |
106
+ | `antigen_sequence` | `string` | Amino acid sequence of the antigen. |
107
+ | `is_expressed` | `boolean` | Whether the candidate is expressed in at least one sample. |
108
+
109
+ ### Dynamic Concentration Columns
110
+
111
+ <Note>
112
+ In addition to the fixed columns above, this table contains **dynamic columns** for each antigen concentration used in the experiment. The column names follow the pattern `log_specificity_score_{conc}nM` and `log_specificity_score_{conc}nM_std`.
113
+ </Note>
114
+
115
+ For our standard workflow, you will see these additional columns:
116
+
117
+ | Column | Type | Description |
118
+ | :--- | :--- | :--- |
119
+ | `log_specificity_score_5nM` | `float` | Mean log specificity score at 5 nM. |
120
+ | `log_specificity_score_5nM_std` | `float` | Standard error of the log specificity score at 5 nM. |
121
+ | `log_specificity_score_50nM` | `float` | Mean log specificity score at 50 nM. |
122
+ | `log_specificity_score_50nM_std` | `float` | Standard error of the log specificity score at 50 nM. |
123
+ | `log_specificity_score_500nM` | `float` | Mean log specificity score at 500 nM. |
124
+ | `log_specificity_score_500nM_std` | `float` | Standard error of the log specificity score at 500 nM. |
125
+
126
+ ---
127
+
128
+ ## Replicate Specificity Scores
129
+
130
+ **File:** `replicate-specificity-scores-YYYYMMDD.parquet`
131
+
132
+ Per-replicate specificity scores unrolled across antigen concentrations. Each row represents a single candidate measured in a specific expression/binding sample pair at a specific antigen concentration. Use this table to inspect replicate-level variation.
133
+
134
+ **Grain:** one row per `(candidate_id, binding_sample_id, antigen_concentration_nM)`.
135
+
136
+ | Column | Type | Nullable | Description |
137
+ | :--- | :--- | :--- | :--- |
138
+ | `candidate_library_id` | `string` | no | Identifier of the candidate library consumed by this sample. |
139
+ | `expression_sample_id` | `string` | no | Sample identifier for the expression (base) sample. |
140
+ | `binding_sample_id` | `string` | no | Sample identifier for the binding (dose) sample. |
141
+ | `candidate_name` | `string` | no | Customer-provided sequence name. |
142
+ | `candidate_id` | `string` | no | Blake-3 content digest of the reference sequence. |
143
+ | `candidate_sequence` | `string` | no | The candidate amino acid sequence. |
144
+ | `variant_id` | `string` | no | Blake-3 content digest of the variant sequence. |
145
+ | `variant_sequence` | `string` | no | The variant sequence. |
146
+ | `sino_catalog_id` | `string` | no | Sino catalog identifier for the antigen. |
147
+ | `antigen_gene_name` | `string` | no | Gene name of the antigen. |
148
+ | `antigen_sequence` | `string` | no | Amino acid sequence of the antigen. |
149
+ | `antigen_concentration_nM` | `float` | no | Antigen concentration in nanomolar. |
150
+ | `is_expressed` | `boolean` | no | Whether the candidate is expressed. |
151
+ | `log_specificity_score` | `float` | yes | Log specificity score. Null when UMI count thresholds are not met. |
152
+
153
+ **Key relationships:**
154
+ - `expression_sample_id` and `binding_sample_id` both correspond to `dim_samples.sample_id`.
155
+ - `candidate_id` is the shared candidate key across all tables.
156
+ - `variant_id` is the shared variant key across all tables.
157
+
158
+ ## Expression Scores
159
+
160
+ **File:** `expression-scores-YYYYMMDD.parquet`
161
+
162
+ Aggregated expression scores per candidate. Expression scores are averaged across replicates.
163
+
164
+ **Grain:** one row per unique `(candidate_id, variant_id)`.
165
+
166
+ ### Fixed Columns
167
+
168
+ | Column | Type | Description |
169
+ | :--- | :--- | :--- |
170
+ | `candidate_library_id` | `string` | Identifier of the candidate library consumed by this sample. |
171
+ | `candidate_name` | `string` | Customer-provided sequence name. |
172
+ | `candidate_id` | `string` | Blake-3 content digest of the reference sequence. |
173
+ | `candidate_sequence` | `string` | The candidate amino acid sequence. |
174
+ | `variant_id` | `string` | Blake-3 content digest of the variant sequence. |
175
+ | `variant_sequence` | `string` | The variant sequence. |
176
+ | `is_expressed` | `boolean` | Whether the candidate is expressed in at least one sample. |
177
+ | `expression_score` | `float` | Mean expression score across all samples. |
178
+ | `expression_score_std` | `float` | Standard error of the expression score across all samples. |
179
+
180
+ ---
181
+
182
+ ## Replicate Expression Scores
183
+
184
+ **File:** `replicate-expression-scores-YYYYMMDD.parquet`
185
+
186
+ Per-replicate expression scores unrolled across different biological replicates. Use this table to inspect replicate-level variation.
187
+
188
+ **Grain:** one row per `(expression_sample_id, candidate_id, variant_id)`.
189
+
190
+ | Column | Type | Nullable | Description |
191
+ | :--- | :--- | :--- | :--- |
192
+ | `candidate_library_id` | `string` | no | Identifier of the candidate library consumed by this sample. |
193
+ | `expression_sample_id` | `string` | no | Sample identifier for the expression (base) sample. |
194
+ | `candidate_name` | `string` | no | Customer-provided sequence name. |
195
+ | `candidate_id` | `string` | no | Blake-3 content digest of the reference sequence. |
196
+ | `candidate_sequence` | `string` | no | The candidate amino acid sequence. |
197
+ | `variant_id` | `string` | no | Blake-3 content digest of the variant sequence. |
198
+ | `variant_sequence` | `string` | no | The variant sequence. |
199
+ | `is_expressed` | `boolean` | no | Whether the candidate is expressed. |
200
+ | `expression_score` | `float` | yes | Expression score derived from the log enrichment from synthesis to expression. Null when UMI count thresholds are not met. |
201
+
202
+ **Key relationships:**
203
+ - `expression_sample_id` corresponds to `dim_samples.sample_id`.
204
+ - `candidate_id` is the shared candidate key across all tables.
205
+ - `variant_id` is the shared variant key across all tables.
README.md CHANGED
@@ -1,29 +1,28 @@
1
  ---
2
  configs:
3
- - config_name: binding_scores
4
- data_files:
5
- - split: train
6
- path: "binding_scores/**/*.parquet"
7
- - config_name: replicate_binding_scores
8
- data_files:
9
- - split: train
10
- path: "replicate_binding_scores/**/*.parquet"
11
- - config_name: specificity_scores
12
- data_files:
13
- - split: train
14
- path: "specificity_scores/**/*.parquet"
15
- - config_name: replicate_specificity_scores
16
- data_files:
17
- - split: train
18
- path: "replicate_specificity_scores/**/*.parquet"
 
 
 
 
 
 
 
 
19
  license: mit
20
  ---
21
-
22
- The instance `data-lab-demo` contains example datasets generated using [version 26.3](https://instance.bio/docs/release-notes#26-3-2026-06-30) of the [instance Data Lab](https://instance.bio/docs/dataset-docs/overview) process.
23
-
24
- For a more thorough explanation, refer to the [Instance Data Lab](./Instance%20Data%20Lab.pdf) report.
25
-
26
- ## Dataset Schemas
27
-
28
- - [`binding_scores` and `replicate_binding_scores`](https://instance.bio/docs/dataset-docs/binding-scores)
29
- - [`specificity_scores` and `replicate_specificity_scores`](https://instance.bio/docs/dataset-docs/specificity-scores)
 
1
  ---
2
  configs:
3
+ - config_name: expression_scores
4
+ data_files:
5
+ - split: train
6
+ path: "expression_scores/**/*.parquet"
7
+ - config_name: replicate_expression_scores
8
+ data_files:
9
+ - split: train
10
+ path: "replicate_expression_scores/**/*.parquet"
11
+ - config_name: binding_scores
12
+ data_files:
13
+ - split: train
14
+ path: "binding_scores/**/*.parquet"
15
+ - config_name: replicate_binding_scores
16
+ data_files:
17
+ - split: train
18
+ path: "replicate_binding_scores/**/*.parquet"
19
+ - config_name: specificity_scores
20
+ data_files:
21
+ - split: train
22
+ path: "specificity_scores/**/*.parquet"
23
+ - config_name: replicate_specificity_scores
24
+ data_files:
25
+ - split: train
26
+ path: "replicate_specificity_scores/**/*.parquet"
27
  license: mit
28
  ---
 
 
 
 
 
 
 
 
 
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