SALT: a fast, memoryefficient and SNPaware short read alignment tool DNA sequence alignment tools play an essential role in genomics and genetics. The accuracy of the alignment directly affects the accuracy of downstream analysis, such as variant calling, so it is essential to map reads to the reference genome rapidly and accurately. It has become an essential topic in the field of bioinformatics. Conventional read aligners map reads to a linear reference genome (such as GRCh38 primary). However, the linear reference genome only represents one or a few individuals of genomes, which lacks the variation information in population. It can introduce bias and impact sensitivity and accuracy of mapping. Recently, a few aligners are beginning to map reads to a graph that captures the entire human genome along with a large number of variants. However, compared to linear reference aligners, storing and indexing all genetic variants require costly memory(RAM) space and make extremely long runtime. Aligning reads to a graph modelbased index, including the whole set of variants, is ultimately an NPhard problem in theory. Considering only SNPs information will reduce the complexity of index and improve the speed of alignments. Herein, we present an SNPaware alignment tool (SALT) that aligns reads to a reference genome that incorporates the SNP database. The SALT is benchmarked both on simulated reads and the real dataset. The results demonstrate that SALT can efficiently map reads to the reference genome, and significantly improve accuracy and sensitivity. Read alignment incorporating SNPs information can improve the sensitivity and accuracy of the read alignment. Moreover, it helps to discover novel variants. SALT is distributed under the GNU General Public License (GPL). Source code is freely available at https:github.comweiquanSALT.

MemAlign: A Memory Structure to Accelerate Gene Sequencing Since 2003, when the human reference genome was discovered, several applications found gene sequencing a promising mechanism to help improve their results. These include studying hereditary diseases, prenatal monitoring and others. Gene sequencing in its typical configuration consists of several elaborate processing stages, each performed by a separate software package. The intermediate results are transferred via large files between gene sequencing different steps, hence making gene sequencing a processing and IO demanding task. Taking advantage of advances memory speed and capacity and with the ultimate goal of pipelining the gene sequencing steps and avoiding utilizing file storage to communicate intermediate results, in this paper we present MemAlign, a novel presorted memory structure to pipeline the first and second processing steps of gene sequencing; Alignment and Sort. The number of memory locations of MemAlign corresponds the positions on the human reference genome. Combined with techniques to compress the alignment results, MemAlign essentially eliminates the Sort step by storing alignment results in the memory location that corresponds to the alignment position. MemAlign not only speeds up the combined processing time of Alignment and Sort, but also saves the considerable amount of storage required to store the intermediate results between the two steps.