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sort samtools sort -o sorted_out unsorted_in.bam. Read the specified unsorted_in.bam as input, sort it by aligned read position, and write it out to sorted_out. Type of output can be either sam, bam, or cram, and will be determined automatically by sorted_out's file-extension. samtools sort -m 5000000 unsorted_in.bam sorted_out
A database index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and storage space to maintain the index data structure. Indexes are used to quickly locate data without having to search every row in a database table every time said table is accessed.
The binary equivalent of a SAM file is a Binary Alignment Map (BAM) file, which stores the same data in a compressed binary representation. [4] SAM files can be analysed and edited with the software SAMtools. [1] The header section must be prior to the alignment section if it is present.
www.htslib.org /doc /samtools-mpileup.html Pileup format is a text-based format for summarizing the base calls of aligned reads to a reference sequence. This format facilitates visual display of SNP /indel calling and alignment.
A range query is a common database operation that retrieves all records where some value is between an upper and lower boundary. [1] For example, list all employees with 3 to 5 years' experience. Range queries are unusual because it is not generally known in advance how many entries a range query will return, or if it will return any at all.
In computer science, an inverted index (also referred to as a postings list, postings file, or inverted file) is a database index storing a mapping from content, such as words or numbers, to its locations in a table, or in a document or a set of documents (named in contrast to a forward index, which maps from documents to content). [1]
A Block Range Index or BRIN is a database indexing technique. They are intended to improve performance with extremely large [ i ] tables. BRIN indexes provide similar benefits to horizontal partitioning or sharding but without needing to explicitly declare partitions.
Database partitioning emerged in the 1980s with systems like Teradata and NonStop SQL.The approach was later adopted by NoSQL databases and Hadoop-based data warehouses.. While implementations vary between transactional and analytical workloads, the core principles of partitioning remain consistent across both use c