You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data 
Chapter Title:  Database and Resources for Variant Filtration. 
1. Abstract of Cited Paper (BIB001):  The completion of the human genome project has initiated, as well as provided the basis for, the collection and study of all sequence variation between individuals. Direct access to up-to-date information on sequence variation is currently provided most efficiently through web-based, gene-centered, locus-specific databases (LSDBs). We have developed the Leiden Open (source) Variation Database (LOVD) software approaching the "LSDB-in-a-Box" idea for the easy creation and maintenance of a fully web-based gene sequence variation database. LOVD is platform-independent and uses PHP and MySQL open source software only. The basic gene-centered and modular design of the database follows the recommendations of the Human Genome Variation Society (HGVS) and focuses on the collection and display of DNA sequence variations. With minimal effort, the LOVD platform is extendable with clinical data. The open set-up should both facilitate and promote functional extension with scripts written by the community. The LOVD software is freely available from the Leiden Muscular Dystrophy pages (www.DMD.nl/LOVD/). To promote the use of LOVD, we currently offer curators the possibility to set up an LSDB on our Leiden server. 
2. Abstract of Cited Paper (BIB002):  Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). The resulting catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We show that this catalogue can be used to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; we identify 3,230 genes with near-complete depletion of truncating variants, 72% of which have no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes.

Literature Review:
During the annotation process, many resources and databases could be used as filtering criteria for detecting novel variants from common polymorphisms. These databases score a variant by its minor allelic frequency (MAF) within a specific population or study. The need for filtration of variants based on this number is subject to the purpose of the study. For example, Mendelian studies would be interested in including common SNVs while cancer studies usually focus on rare variants found in less than 1% of the population. NCBI dbSNP database, established in 2001, is an evolving database containing both well-known and rare variants from many organisms BIB001 . dbSNP also contains additional information including disease association, genotype origin, and somatic and germline variant information BIB001 . The Leiden Open Variation Database (LOVD) developed in 2005 links its database to several other repositories so that the user can make comparisons and gain further information BIB002 . One of the most popular SNV databases was developed in 2010 from the 1000 Genomes Project that uses statistics from the sequencing of more than 1000 "healthy" people of all ethnicities [41] . This is especially helpful for cancer studies, as damaging mutations found in cancer are often very rare in a healthy population. Another database essential for cancer studies is the Catalogue of Somatic Mutations In Cancer (COSMIC)  . This database of somatic mutations found in cancer studies from almost 20,000 publications allows for identification of potentially important cancer-related variants. More recently, the Exome Aggregation Consortium (ExAC) has assembled and reanalyzed WES data of 60,706 unrelated individuals from various disease-specific and population genetic studies BIB003 . The ExAC web portal and data provide a resource for assessing the significance of variants detected in WES data BIB003 .