Difference between revisions of "HLAminer"
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| − | The HLA prediction by targeted assembly of short sequence reads (HPTASR), performs targeted de novo assembly of HLA NGS reads and align the resulting contigs to reference HLA alleles from the IMGT/HLA sequence repository using commodity hardware with standard specifications (<2GB RAM, 2GHz). Putative HLA types are inferred by mining and scoring the contig alignments and an expect value is determined for each. The method is accurate, simple and fast to execute and, for transcriptome data, requires low depth of coverage. Known HLA class I/class II reference sequences available from the IMGT/HLA public repository are read by TASR using default options (Warren and Holt 2011) to create a hash table of all possible 15 nt words (k-mers) from these reference sequences. Note that this parameter is customizable and larger k values will yield predictions with increased specificity (at the possible expense of sensitivity). Subsequently, NGS data sets are interrogated for the presence of one of these kmers (on either strand) at the 5’ or 3’ start. Whenever an HLA word is identified, the read is recruited as a candidate for de novo assembly. Upon de novo assembly of all recruited reads, a set of contigs is generated. Only sequence contigs equal or larger than 200nt in length are considered for further analysis, as longer contigs better resolve HLA allelic variants. Reciprocal BLASTN alignments are performed between the contigs and all HLA allelic reference sequences. HPTASR mines the alignments, scoring each possible HLA allele identified, computing and reporting an expect value (E-value) based on the chance of contigs characterizing given HLA alleles and, reciprocally, the chance of reference HLA alleles aligning best to certain assembled contig sequences | + | The HLA prediction by targeted assembly of short sequence reads (HPTASR), performs targeted de novo assembly of HLA NGS reads and align the resulting contigs to reference HLA alleles from the IMGT/HLA sequence repository using commodity hardware with standard specifications (<2GB RAM, 2GHz). Putative HLA types are inferred by mining and scoring the contig alignments and an expect value is determined for each. The method is accurate, simple and fast to execute and, for transcriptome data, requires low depth of coverage. Known HLA class I/class II reference sequences available from the IMGT/HLA public repository are read by TASR using default options (Warren and Holt 2011) to create a hash table of all possible 15 nt words (k-mers) from these reference sequences. Note that this parameter is customizable and larger k values will yield predictions with increased specificity (at the possible expense of sensitivity). <br> |
| + | Subsequently, NGS data sets are interrogated for the presence of one of these kmers (on either strand) at the 5’ or 3’ start. Whenever an HLA word is identified, the read is recruited as a candidate for de novo assembly. Upon de novo assembly of all recruited reads, a set of contigs is generated. Only sequence contigs equal or larger than 200nt in length are considered for further analysis, as longer contigs better resolve HLA allelic variants. Reciprocal BLASTN alignments are performed between the contigs and all HLA allelic reference sequences. HPTASR mines the alignments, scoring each possible HLA allele identified, computing and reporting an expect value (E-value) based on the chance of contigs characterizing given HLA alleles and, reciprocally, the chance of reference HLA alleles aligning best to certain assembled contig sequences | ||
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Latest revision as of 14:55, 14 December 2022
Description
The HLA prediction by targeted assembly of short sequence reads (HPTASR), performs targeted de novo assembly of HLA NGS reads and align the resulting contigs to reference HLA alleles from the IMGT/HLA sequence repository using commodity hardware with standard specifications (<2GB RAM, 2GHz). Putative HLA types are inferred by mining and scoring the contig alignments and an expect value is determined for each. The method is accurate, simple and fast to execute and, for transcriptome data, requires low depth of coverage. Known HLA class I/class II reference sequences available from the IMGT/HLA public repository are read by TASR using default options (Warren and Holt 2011) to create a hash table of all possible 15 nt words (k-mers) from these reference sequences. Note that this parameter is customizable and larger k values will yield predictions with increased specificity (at the possible expense of sensitivity).
Subsequently, NGS data sets are interrogated for the presence of one of these kmers (on either strand) at the 5’ or 3’ start. Whenever an HLA word is identified, the read is recruited as a candidate for de novo assembly. Upon de novo assembly of all recruited reads, a set of contigs is generated. Only sequence contigs equal or larger than 200nt in length are considered for further analysis, as longer contigs better resolve HLA allelic variants. Reciprocal BLASTN alignments are performed between the contigs and all HLA allelic reference sequences. HPTASR mines the alignments, scoring each possible HLA allele identified, computing and reporting an expect value (E-value) based on the chance of contigs characterizing given HLA alleles and, reciprocally, the chance of reference HLA alleles aligning best to certain assembled contig sequences
Environment Modules
Run module spider hlaminer to find out what environment modules are available for this application.
System Variables
- HPC_HLAMINER_DIR - installation directory
- HPC_HLAMINER_BIN - executable directory
Citation
If you publish research that uses hlaminer you have to cite it as follows: