Datasets:

songlab
/

deprecated-full-gnomad

chrom stringclasses 2 values	pos int64 10.2k 249M	ref stringclasses 4 values	alt stringclasses 4 values	AC int64 1 152k	AN int64 2 152k	AF float64 0 1	consequence stringlengths 9 552	GPN-MSA float32 -13.59 11.1
1	10,181	A	T	56	520	0.107692	TF_binding_site_variant,downstream_gene_variant,regulatory_region_variant,upstream_gene_variant	-0.36925
1	10,193	A	T	1	25,386	0.000039	downstream_gene_variant,regulatory_region_variant,upstream_gene_variant	-0.429617
1	10,202	C	G	1	71,460	0.000014	downstream_gene_variant,regulatory_region_variant,upstream_gene_variant	-2.82533
1	10,367	C	T	33	133,014	0.000248	TF_binding_site_variant,downstream_gene_variant,regulatory_region_variant,upstream_gene_variant	-0.602358
1	10,376	A	C	1	49,706	0.00002	TF_binding_site_variant,downstream_gene_variant,regulatory_region_variant,upstream_gene_variant	0.382358
1	10,477	C	T	6	59,882	0.0001	downstream_gene_variant,upstream_gene_variant	-0.586057
1	10,482	G	A	2	44,458	0.000045	downstream_gene_variant,upstream_gene_variant	-0.85981
1	10,483	C	A	3	68,770	0.000044	downstream_gene_variant,upstream_gene_variant	-0.857589
1	10,483	C	G	1	68,772	0.000015	downstream_gene_variant,upstream_gene_variant	-0.35157
1	10,486	G	A	1	51,532	0.000019	downstream_gene_variant,upstream_gene_variant	-0.56156
1	10,486	G	C	2	51,532	0.000039	downstream_gene_variant,upstream_gene_variant	0.384257
1	10,489	C	T	3	75,980	0.000039	downstream_gene_variant,upstream_gene_variant	0.143523
1	10,490	G	A	19	56,492	0.000336	downstream_gene_variant,upstream_gene_variant	0.347739
1	10,490	G	T	3	56,504	0.000053	downstream_gene_variant,upstream_gene_variant	0.491265
1	10,491	C	G	1	85,100	0.000012	downstream_gene_variant,upstream_gene_variant	-0.096123
1	10,492	C	T	1,697	58,906	0.028809	downstream_gene_variant,upstream_gene_variant	-0.676649
1	10,493	C	G	59	76,212	0.000774	downstream_gene_variant,upstream_gene_variant	-0.164748
1	10,494	G	A	2	63,500	0.000031	downstream_gene_variant,upstream_gene_variant	0.305827
1	10,498	G	T	3	67,980	0.000044	downstream_gene_variant,upstream_gene_variant	0.474117
1	10,503	T	C	4	72,034	0.000056	downstream_gene_variant,upstream_gene_variant	-0.149619
1	10,504	G	C	46	72,160	0.000637	downstream_gene_variant,upstream_gene_variant	0.288704
1	10,506	C	G	1	77,026	0.000013	downstream_gene_variant,upstream_gene_variant	0.262592
1	10,511	G	C	2	75,410	0.000027	downstream_gene_variant,upstream_gene_variant	-1.173397
1	10,513	A	G	1	77,566	0.000013	downstream_gene_variant,upstream_gene_variant	0.011212
1	10,513	A	T	1	77,570	0.000013	downstream_gene_variant,upstream_gene_variant	-0.405044
1	10,514	G	C	1	76,640	0.000013	downstream_gene_variant,upstream_gene_variant	-0.225178
1	10,515	A	C	1	75,396	0.000013	downstream_gene_variant,upstream_gene_variant	0.480822
1	10,515	A	G	2	75,396	0.000027	downstream_gene_variant,upstream_gene_variant	0.389552
1	10,518	T	C	2	75,128	0.000027	downstream_gene_variant,upstream_gene_variant	-0.041974
1	10,519	G	A	1	62,980	0.000016	downstream_gene_variant,upstream_gene_variant	-1.177571
1	10,533	G	C	26	57,474	0.000452	downstream_gene_variant,upstream_gene_variant	0.030623
1	10,536	T	A	1	71,426	0.000014	downstream_gene_variant,upstream_gene_variant	0.791045
1	10,536	T	C	1	71,426	0.000014	downstream_gene_variant,upstream_gene_variant	1.160853
1	10,539	C	A	3	73,730	0.000041	downstream_gene_variant,upstream_gene_variant	-0.718854
1	10,543	G	A	3	72,936	0.000041	downstream_gene_variant,upstream_gene_variant	0.486537
1	10,550	G	A	1	71,906	0.000014	downstream_gene_variant,upstream_gene_variant	-0.987967
1	10,555	G	C	4	70,304	0.000057	downstream_gene_variant,upstream_gene_variant	-0.267843
1	10,558	G	C	1	68,376	0.000015	downstream_gene_variant,upstream_gene_variant	0.006382
1	10,563	C	A	16	67,114	0.000238	downstream_gene_variant,upstream_gene_variant	0.517038
1	10,563	C	T	3	67,120	0.000045	downstream_gene_variant,upstream_gene_variant	0.177246
1	10,565	C	T	1	66,612	0.000015	downstream_gene_variant,upstream_gene_variant	-1.272811
1	10,567	G	A	2	66,148	0.00003	downstream_gene_variant,upstream_gene_variant	-0.848526
1	10,571	C	T	1	63,484	0.000016	downstream_gene_variant,upstream_gene_variant	0.186047
1	10,575	C	G	2	60,576	0.000033	downstream_gene_variant,upstream_gene_variant	-0.753386
1	10,578	G	C	2	49,726	0.00004	downstream_gene_variant,upstream_gene_variant	0.638552
1	10,581	G	A	1	54,718	0.000018	downstream_gene_variant,upstream_gene_variant	-0.921889
1	10,582	T	C	5	53,586	0.000093	downstream_gene_variant,upstream_gene_variant	0.501172
1	10,583	G	A	325	42,096	0.00772	downstream_gene_variant,upstream_gene_variant	-1.280454
1	10,584	C	A	1	51,646	0.000019	downstream_gene_variant,upstream_gene_variant	-0.963778
1	10,590	G	C	2	49,220	0.000041	downstream_gene_variant,upstream_gene_variant	-0.033042
1	10,593	T	C	9	45,992	0.000196	downstream_gene_variant,upstream_gene_variant	0.688872
1	10,596	G	C	1	45,330	0.000022	downstream_gene_variant,upstream_gene_variant	0.310133
1	10,598	G	A	1	44,458	0.000022	downstream_gene_variant,upstream_gene_variant	-1.321086
1	10,601	G	A	1	41,000	0.000024	downstream_gene_variant,upstream_gene_variant	-1.342886
1	10,748	G	C	7	102,808	0.000068	downstream_gene_variant,upstream_gene_variant	-0.373331
1	10,762	C	G	3	107,182	0.000028	downstream_gene_variant,upstream_gene_variant	0.179545
1	10,765	G	A	1	105,572	0.000009	downstream_gene_variant,upstream_gene_variant	-1.172967
1	10,770	G	C	45	104,044	0.000433	downstream_gene_variant,upstream_gene_variant	-0.477708
1	10,777	G	C	3	87,284	0.000034	downstream_gene_variant,upstream_gene_variant	-0.352492
1	10,785	C	T	7	63,680	0.00011	downstream_gene_variant,upstream_gene_variant	-1.32269
1	10,796	G	A	1	36,246	0.000028	downstream_gene_variant,upstream_gene_variant	-1.084151
1	10,801	C	G	2	23,032	0.000087	downstream_gene_variant,upstream_gene_variant	0.369517
1	10,804	A	C	1	17,998	0.000056	downstream_gene_variant,upstream_gene_variant	1.375888
1	10,812	G	C	10	11,546	0.000866	downstream_gene_variant,upstream_gene_variant	-0.237664
1	10,817	G	A	1	9,734	0.000103	downstream_gene_variant,upstream_gene_variant	-0.522754
1	10,817	G	C	7	9,734	0.000719	downstream_gene_variant,upstream_gene_variant	-0.163188
1	10,818	G	A	6	47,878	0.000125	downstream_gene_variant,upstream_gene_variant	-0.699162
1	10,818	G	T	1	47,878	0.000021	downstream_gene_variant,upstream_gene_variant	-0.928654
1	10,825	G	A	1	47,736	0.000021	downstream_gene_variant,upstream_gene_variant	-1.117587
1	10,835	A	C	1	42,756	0.000023	downstream_gene_variant,upstream_gene_variant	0.377916
1	10,837	G	C	1	44,860	0.000022	downstream_gene_variant,upstream_gene_variant	-0.167094
1	10,847	G	C	2	43,232	0.000046	downstream_gene_variant,upstream_gene_variant	-0.061229
1	10,875	C	T	2	38,914	0.000051	downstream_gene_variant,upstream_gene_variant	-1.419405
1	10,888	G	T	1	36,510	0.000027	downstream_gene_variant,upstream_gene_variant	-0.378293
1	10,918	G	C	1	36,980	0.000027	downstream_gene_variant,upstream_gene_variant	-0.479087
1	10,928	C	A	2	29,822	0.000067	downstream_gene_variant,upstream_gene_variant	-1.045573
1	10,932	G	A	1	28,962	0.000035	downstream_gene_variant,upstream_gene_variant	-0.757578
1	10,946	A	G	1	24,878	0.00004	downstream_gene_variant,upstream_gene_variant	0.287965
1	10,959	A	G	1	19,964	0.00005	downstream_gene_variant,upstream_gene_variant	1.56442
1	10,964	G	C	19	18,646	0.001019	downstream_gene_variant,upstream_gene_variant	0.548674
1	10,972	G	A	12	17,570	0.000683	downstream_gene_variant,upstream_gene_variant	-0.979231
1	10,975	G	C	1	16,950	0.000059	downstream_gene_variant,upstream_gene_variant	-0.240667
1	10,977	G	T	1	16,102	0.000062	downstream_gene_variant,upstream_gene_variant	-1.392421
1	11,014	G	A	26	4,510	0.005765	downstream_gene_variant,upstream_gene_variant	-0.609987
1	11,021	G	C	1	3,614	0.000277	downstream_gene_variant,upstream_gene_variant	-0.148484
1	11,022	G	A	34	2,972	0.01144	downstream_gene_variant,upstream_gene_variant	-0.139792
1	11,023	G	A	1	3,280	0.000305	downstream_gene_variant,upstream_gene_variant	0.034881
1	11,030	G	A	2	1,914	0.001045	downstream_gene_variant,upstream_gene_variant	-1.76514
1	11,125	G	C	1	244	0.004098	downstream_gene_variant,upstream_gene_variant	-0.441182
1	11,134	A	G	2	226	0.00885	downstream_gene_variant,upstream_gene_variant	1.095121
1	12,998	C	G	1	111,102	0.000009	downstream_gene_variant,intron_variant&non_coding_transcript_variant,non_coding_transcript_exon_variant	-6.365894
1	13,007	G	C	1	115,132	0.000009	downstream_gene_variant,intron_variant&non_coding_transcript_variant,non_coding_transcript_exon_variant	-4.583621
1	13,014	T	C	1	116,866	0.000009	downstream_gene_variant,intron_variant&non_coding_transcript_variant,non_coding_transcript_exon_variant	-4.555737
1	13,023	T	C	1	119,678	0.000008	downstream_gene_variant,intron_variant&non_coding_transcript_variant,non_coding_transcript_exon_variant	-4.339008
1	13,031	A	G	2	121,810	0.000016	downstream_gene_variant,intron_variant&non_coding_transcript_variant,non_coding_transcript_exon_variant	-5.868319
1	13,037	G	A	2	122,950	0.000016	downstream_gene_variant,intron_variant&non_coding_transcript_variant,non_coding_transcript_exon_variant	-5.091455
1	13,047	C	A	2	124,394	0.000016	downstream_gene_variant,intron_variant&non_coding_transcript_variant,non_coding_transcript_exon_variant	-6.206705
1	13,052	G	C	4	125,182	0.000032	downstream_gene_variant,intron_variant&non_coding_transcript_variant,splice_region_variant&non_coding_transcript_exon_variant	-6.405015
1	13,053	G	C	44	125,134	0.000352	downstream_gene_variant,intron_variant&non_coding_transcript_variant,splice_donor_variant&non_coding_transcript_variant	-7.536184
1	13,073	C	A	1	126,460	0.000008	downstream_gene_variant,intron_variant&non_coding_transcript_variant	-1.72454

End of preview. Expand in Dataset Viewer.

gnomAD variants and GPN-MSA predictions

For more information check out our paper and repository.

Querying specific variants or genes

Install the latest tabix:
In your current conda environment (might be slow):

conda install -c bioconda -c conda-forge htslib=1.18

or in a new conda environment:

conda create -n tabix -c bioconda -c conda-forge htslib=1.18
conda activate tabix

Query a specific region (e.g. BRCA1), from the remote file:

tabix https://huggingface.co/datasets/songlab/gnomad/resolve/main/scores.tsv.bgz 17:43,044,295-43,125,364

The output has the following columns:
| chrom | pos | ref | alt | GPN-MSA score |
and would start like this:

17      43044304        T       G       -5.10
17      43044309        A       G       -3.27

17 43044315 T A -6.84 17 43044320 T C -6.19 17 43044322 G T -5.29 17 43044326 T G -3.22 17 43044342 T C -4.10 17 43044346 C T -2.06 17 43044351 C T -0.33 17 43044352 G A 2.05

- If you want to do many queries you might want to first download the files locally
```bash
wget https://huggingface.co/datasets/songlab/gnomad/resolve/main/scores.tsv.bgz
wget https://huggingface.co/datasets/songlab/gnomad/resolve/main/scores.tsv.bgz.tbi

and then score:

tabix scores.tsv.bgz 17:43,044,295-43,125,364

Large-scale analysis

test.parquet contains coordinates, scores, plus allele frequency and consequences. Download:

wget https://huggingface.co/datasets/songlab/gnomad/resolve/main/test.parquet

Load into a Pandas dataframe:

df = pd.read_parquet("test.parquet")

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Size of the auto-converted Parquet files (First 5GB):

840 MB

Number of rows (First 5GB):

45,270,000