SpliceAI is a deep neural network that accurately predicts splice junctions from an arbitrary pre-mRNA transcript sequence, enabling precise prediction of noncoding genetic variants that cause cryptic splicing.

References:

• Kishore Jaganathan, Sofia Kyriazopoulou Panagiotopoulou, Jeremy F. McRae, et al.
  Predicting Splicing from Primary Sequence with Deep Learning , Cell 176, 535–548, January 24, 2019

• SpliceAI GitHub page

• Module Name: SpliceAI (see the modules page for more information)
• Singlethreaded
• Unusual environment variables set
  • SPLICEAI_HOME   installation directory
  • SPLICEAI_BIN         executable directory
  • SPLICEAI_DATA     sample data directory
  • SPLICEAI_SRC       source code directory

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive --mem=8g --gres=gpu:v100:1
[user@cn4466 ~]$ module load SpliceAI
+] Loading python 3.6  ...
[+] Loading cuDNN 7.0  libraries...
[+] Loading CUDA Toolkit  9.0.176  ...
[user@cn4466 ~]$ spliceai -h
...
usage: spliceai [-h] [-I [input]] [-O [output]] -R reference -A annotation
                [-D [distance]] [-M [mask]]

Version: 1.3

optional arguments:
  -h, --help     show this help message and exit
  -I [input]     path to the input VCF file, defaults to standard in
  -O [output]    path to the output VCF file, defaults to standard out
  -R reference   path to the reference genome fasta file
  -A annotation  "grch37" (GENCODE V24lift37 canonical annotation file in
                 package), "grch38" (GENCODE V24 canonical annotation file in
                 package), or path to a similar custom gene annotation file
  -D [distance]  maximum distance between the variant and gained/lost splice
                 site, defaults to 50
  -M [mask]      mask scores representing annotated acceptor/donor gain and
                 unannotated acceptor/donor loss, defaults to 0

[user@cn4466 ~]$ cp $SPLICEAI_DATA/* . 

[user@cn4466 ~]$ ln -s  /fdb/igenomes/Homo_sapiens/UCSC/hg38/Sequence/WholeGenomeFasta/genome.fa hg38.fa

 
[user@cn4466 ~]$ spliceai -I input.vcf -O output.vcf -R hg38.fa  -A grch37 & 
...
[user@cn4466 ~]$ nvidia-smi
...
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.126.09             Driver Version: 580.126.09     CUDA Version: 13.0     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  Tesla V100-PCIE-16GB           On  |   00000000:8E:00.0 Off |                    0 |
| N/A   27C    P0             24W /  250W |       0MiB /  16384MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A     45210      C   /usr/bin/python                 11616MiB |
+-----------------------------------------------------------------------------+
...
WARNING:root:Skipping record (ref issue): 2     152389953       .       T       A,C,G   .       .       .

WARNING:root:Skipping record (ref issue): 2     179415988       .       C       CA      .       .       .

WARNING:root:Skipping record (ref issue): 2     179446218       .       ATACT   A       .       .       .

WARNING:root:Skipping record (ref issue): 2     179446218       .       ATACT   AT,ATA  .       .       .

WARNING:root:Skipping record (ref issue): 2     179642185       .       G       A       .       .       .

WARNING:root:Skipping record (ref issue): 19    38958362        .       C       T       .       .       .

WARNING:root:Skipping record (ref issue): 21    47406854        .       CCA     C       .       .       .

WARNING:root:Skipping record (ref issue): 21    47406856        .       A       AT      .       .       .

WARNING:root:Skipping record (ref issue): X     129274636       .       A       C,G,T   .       .       .

[user@cn4466 ~]$ cat output.vcf
...
#CHROM  POS     ID      REF     ALT     QUAL    FILTER  INFO
1       25000   .       A       C,G,T   .       .       .
2       152389953       .       T       A,C,G   .       .       .
2       179415988       .       C       CA      .       .       .
2       179446218       .       ATACT   A       .       .       .
2       179446218       .       ATACT   AT,ATA  .       .       .
2       179642185       .       G       A       .       .       .
19      38958362        .       C       T       .       .       .
21      47406854        .       CCA     C       .       .       .
21      47406856        .       A       AT      .       .       .
X       129274636       .       A       C,G,T   .       .       .

[user@cn4466 ~]$ exit
[user@biowulf ~]$

Create a batch input file (e.g. spliceai.sh). For example:

#!/bin/bash
module load SpliceAI      
cp $SPLICEAI_DATA/* .  
spliceai -I input.vcf -O output.vcf -R /fdb/igenomes/Homo_sapiens/UCSC/hg38/Sequence/WholeGenomeFasta/genome.fa  -A grch37

Submit this job using the Slurm sbatch command.

sbatch [--cpus-per-task=#] [--mem=#] spliceai.sh