UCSC Genome Bioinformatics: Frequently Asked Questions (2023)

Frequently asked questions: Blat

  • Blat against explosion
  • Blat usage restrictions
  • Download the Blat source code and documentation
  • Web-based Blat parameter replication in command-line version
  • Using the -ooc flag
  • Replication of web-based Blat percent identity and score calculations
  • Blat Web Based Search Result Replication "I'm Feeling Lucky"
  • Using Blat for short sequences with maximum sensitivity

Back to FAQ Table of Contents



Blat against explosion

Ask:
"What are the differences between Blat and Blast?"

Response:
Blat is an alignment tool like BLAST, but it has a different structure. In DNA, Blat works by keeping an index of an entire genome in memory. Therefore, the target database for BLAT is not a set of GenBank sequences, but an index derived from whole-genome assembly. The index, which uses less than a gigabyte of RAM, consists of all non-overlapping 11-mers except those heavily involved in repeats. This smaller size means Blat is much easierreflected. Blat of DNA is designed to quickly find 95% or greater similarity sequences that are 40 bases long or more. You can ignore shorter or more divergent sequence alignments.

In proteins, Blat uses 4-mers instead of 11-mers, finding 80% protein sequences and higher similarity with the 20+-length amino acid query. The protein index requires a little more than 2 gigabytes of RAM. In practice, DNABlat works well in humans and primates due to rates of sequence divergence over evolutionary time, whereas the Blat protein continues to find good matches in terrestrial vertebrates and even earlier organisms for conserved proteins. Within humans, the Blat protein provides a much better picture of gene families (paralogs) than the Blat DNA. However, BLAST and psi-BLAST at NCBI can find much more distant matches.

From a practical point of view, Blat has several advantages over BLAST:

  • speed (no queues, responses in seconds) at the cost of less depth of homology
  • the ability to send a long list of simultaneous requests in fasta format
  • five practical output sorting options
  • a direct link to the UCSC browser
  • details of the alignment block in natural genomic sequence
  • an option to start the lineup later as part of a custom track
Blat is commonly used to find the location of a sequence in the genome or determine the exon structure of an mRNA, but expert users can run large batch jobs and make internal parameter sensitivity changes by installing the Blat command line on their own Linux server.


Blat usage restrictions

Ask:
"I received a high traffic warning from your Blatserver informing me that I had exceeded the server's usage limits. Can you provide me with some information about the usage parameters of the UCSCBlat server?"

Response:
Due to the high demand on our Blat servers, we limit the service to users who query Blat programmatically or perform large batch queries. The use of Blat powered by the program is limited to a maximum of one visit every 15 seconds and no more than 5000 visits per day. Limit batch requests to 25 streams or less.

For users with large Blat requirements, we recommend downloading Blat for local use. For more information, seeDownload the Blat source code and documentation.



Download the Blat source code and documentation

Ask:
"Is the Blat font available for download? Is documentation available?"

Response:
Blat's source code and executable files are freely available for personal, academic and non-profit use. Corporate licensing information is available atKent computer website.

The Blat font can be downloaded fromhttp://www.soe.ucsc.edu/~kent(look for the blatSrc* zip file with the latest date). For Blat executables, go tohttp://hgdownload.cse.ucsc.edu/admin/exe/; and select your type of machine.

Documentation on the specifications of the Blat program is availableher.



Web-based Blat parameter replication in command-line version

Ask:
"I'm setting up my own Blat server and would like to use the same parameter values ​​that UCSC's web-based Blat server uses."

Response:
Use the following settings to replicate search results from the UCSC Blat server. Note that you may still notice some slight differences between the command-line results and the web-based results, depending on the search being performed.

fatotwobit:

  • Use soft masking.

servidorgf(this is how the UCSC web-based blat servers are set up):

  • blat-server (PCR compatible):gfServer inicia blatMachine portX -stepSize=5 -log=untrans.log base af datos.2bit
  • blat server translated:
    gfServer iniciar blatMachine portY -trans -mask -log=trans.log base de datas.2bit
To enable DNA/DNA and DNA/RNA matching, only host, port and twoBit files are required. The same port is used for untranslated blat (gfClient) and PCR (webPcr). You need a separate blat server on a separate port to enable translated blat (protein lookup or translated lookup in protein space).

gfCliente:

  • To position-Minimumscore=0y-minIdentities=0. This will result in some low score matches, usually bogus, but for interactive use it's easy enough to ignore (because the results are sorted by score) and sometimes low score matches are useful.

freestanding table:

  • blat search:
    blat -stepSize=5 -repMatch=2253 -minScore=0 -minIdentity=0 base de datos.2bit consulta.fa salida.psl

RepMatch Notes:
The default setting for gfServer DNA matches is: repMatch = 1024 * (tileSize/stepSize).
The default setting for blat dna-matches is: repMatch = 1024 (if tileSize = 11).
To get command-line output that matches web-based output, repMatch must be specified using blat.

For more information about the parameters available for blat, gfServer and gfClient, seespecifications blat.



User-ooobandera

Ask:
“What he does-ooomake the flag?

Response:
possibly uses-ooopossibility in blat, please-ooc=11.ooc, it simply serves to speed up searches in the same way as the masking iteration sequence. He11.oocThe file contains sequences that have been determined to be overrepresented in the genome sequence. To speed up searches, these sequences are not used when an alignment against the genome is seen. For sequences of reasonable size, this will not create a problem and will significantly reduce processing time.

By not using11.oocfile, the fitting time will increase, but the sensitivity will also increase slightly. This can be important if you are setting up shorter or poor quality sequences. For example, if a particular sequence consists primarily of sequences i11.oocfile, it will never seed correctly for a lineup if-oooflag is used.

In short, if you can't find certain streams and can afford the extra processing time, you might want to run blat without11.oocfile if your particular situation warrants its use.



Replication of web-based Blat percent identity and score calculations

Ask:
"Using my own command-line Blat server, how can I replicate the score and identity percentage calculations produced by web-based Blat?"

Response:
There is no command line option for Blat to give you the ID percentage and score. Instead, you will need to write your own program to do the calculations that incorporates some of the features of the Genome Browser source code.

To calculate the ID percentage, integrate the following code and function into a program that processes your Blat PSL output. parameteresMrnamust be set to TRUE regardless of whether the input sequence is mRNA or protein.

The identity score percentage is calculated as follows:

100,0 - pslCalcMilliBad(psl, TRUE) * 0,1

Here is the sourcepslCalcMilliBad:

int pslCalcMilliBad(struct psl *psl, boolean isMrna)/* Calcula la maldad en partes por mil. */{int sizeMul = pslIsProtein(psl) ? 3 : 1;int qAliSize, tAliSize, aliSize;int milliBad = 0;int sizeDif;int insertFactor;int total;qAliSize = sizeMul * (psl->qEnd - psl->qStart);tAliSize = psl->tEnd - psl >tStart;aliSize = min(qAliSize, tAliSize);if (aliSize <= 0) return 0;sizeDif = qAliSize - tAliSize;if (sizeDif < 0) { if (isMrna) sizeDif = 0; más tamañoDif = -tamañoDif; }insertFactor = psl->qNumInsert;if (!isMrna) insertFactor += psl->tNumInsert;total = (sizeMul * (psl->match + psl->repMatch + psl->misMatch));if (total != 0 ) miliBad = (1000 * (psl->misMatch*sizeMul + insertFactor + round(3*log(1+sizeDif)))) / total;return miliBad;}

The complexity of milliBad is mainly due to how it handles stakes. Ignoring interpolation, the calculation is simply discrepancies expressed as parts per thousand. However, the algorithm also takes into account deployment penalties, which are relatively weak compared to, for example, explosions, but are still present. When large insertions are allowed (which are necessary to accommodate introns), it is usually necessary to resort to logarithms, as this calculation does.

HepslIsProteinfunction called bypslCalcMilliBades:

boolean pslIsProtein(const struct psl *psl)/* is psl a protein psl (is the block sizes and scores in protein space) */{int lastBlock = psl->blockCount - 1;return (((psl- >string[ 1] == '+' ) && (psl->tEnd == psl->tStarts[lastBlock] + 3*psl->blockSizes[lastBlock])) || ((psl->string[1] = = '- ') && ( psl->tStart == (psl->tSize-(psl->tStarts[lastBlock] + 3*psl->blockSizes[lastBlock])))));}

This function automatically determines whether the PSL output file contains alignment information for a protein query. Alternatively, you can write the program so that the user specifies whether the query is a protein or not.

The score calculation is generated by the following function:

int pslScore(const struct psl *psl)/* Returnerer scoren for psl. */{int sizeMul = pslIsProtein(psl) ? 3:1; returner sizeMul * (psl->match + ( psl->repMatch>>1)) - sizeMul * psl->misMatch - psl->qNumInsert - psl->tNumInsert;}

For help creating a C program to perform these calculations, you can use the Genome Browser Source Code Libraries. see ourFrequently asked questionsabout source code licenses and downloads for information on how to obtain the source. The filekent/src/lib/psl.ccontainspslCalcMilliBad,pslIsProteinypslScorefunctions and also a useful function calledpslLoadAllwhich loads the psl file into a linked list structure. The definition of the psl structure can be found inkent/src/inc/psl.h.



Blat Web Based Search Result Replication "I'm Feeling Lucky"

Ask:
"How do I generate the same search results as the web-based Blat "I feel lucky" option using the blat command line?"

Response:
The code for Blatsearch "I'm Feeling Lucky" sorts the results based on the output sort option you chose on the query page. It then returns the highest scoring alignment of the first query sequence.

If you sort the results by "query, start" or "chrome, start", generating the "I'm feeling lucky" result is easy: sort the output file by these columns, then select the top result.

To replicate any of the ranking options that involve scoring, first calculate the score for each result in your PSL output file, then sort the results by score or some other combination (p.e."query, score" and "chrome, score"). See the section regardingReplication of web-based Blat percent identity and score calculationsfor information on score calculation.

Alternatively, try filtering your Blat PSL output using thepslRepsopslCDnaFilterprogram available in the source code of GenomeBrowser. For information on how to obtain the source code, see ourFrequently asked questionsabout source code licenses and downloads.



Using Blat for short sequences with maximum sensitivity

Ask:
"How do I set blat to short sequences with maximum sensitivity?"

Response:
Here are some guidelines for configuring standalone blat and gfServer/gfClient for these conditions:

  • The formula for finding the shortest query size that guarantees a match (if the matching fields are not marked as overused) is: 2 *step size+tile size- 1
    For example withstep sizeset to 5 andtile sizeset to 11, matches with query size 2 * 5 + 11 - 1 = 20 bp will be found if the query exactly matches the target.
    Hestep sizeThe parameter can vary from 1 totile size.
    Hetile sizeThe parameter can vary from 6 to 15. For proteins, the interval starts lower.
    Tominimal fest=1 (e.g. protein), the minimum guaranteed duration of the match is: 1 *step size+tile size- 1
  • try to use-WELL.
  • Use a large value forreplay the match(p.e.-repPartido= 1000000) to reduce the risk of a tile being marked as overused.
  • Don't wear one.oocfile.
  • Do not use- quick map.
  • Do not use masking command line options.

The above changes will make BLAT more responsive, but will also slow down and increase memory usage. It may be necessary to process one chromosome at a time to reduce memory requirements.

A note about output filtering: increase- minimumscoreparameter value beyond half the query size has no further effect. Therefore, usepslRepsopslCDnaFilterprogram available in the Genome Browser source code to filter by desired size, score, coverage, or quality. For information on how to obtain the source code, see ourFrequently asked questionsabout source code licenses and downloads.


FAQs

What is the difference between UCSC and Ensembl Genome Browser? ›

Ensembl uses a one-based coordinate system, whereas UCSC uses a zero-based coordinate system. Ensembl uses the most recently updated human genome housed at the GRC. This current major assembly release is called GRCh38. NCBI and UCSC use the same genome.

Why do we use UCSC Genome Browser? ›

It allows control over the style of sequencing displayed (e.g., genomic coordinates, sequences, gaps etc.). It can also display a percentage based track to show a researcher if a particular genetic element is more prevalent in the specified area.

What is the difference between Gencode and Ensembl? ›

What is the difference between GENCODE GTF and Ensembl GTF? The gene annotation is the same in both files. The only exception is that the genes which are common to the human chromosome X and Y PAR regions can be found twice in the GENCODE GTF, while they are shown only for chromosome X in the Ensembl file.

What is the difference between Ensembl and RefSeq? ›

The basic difference is that RefSeq is a collection of non-redundant, curated mRNA models, whereas Ensembl is a database containing more gene models from multiple sources, mapped to the reference genome. That question has more to do with Entrez Gene than Entrez RefSeq.

What are the three main genome browsers? ›

Features and functionality
Genome browserDatabase(s)
NCBI Genome Data viewerAssembly Conserved Domain database RefSeq database PubMed GenBank
JBrowseGMOD (Generic Model Organism Database)
Integrated Genome Viewer (IGV)Not tied to a specific database, can load data from various sources
2 more rows

How to get DNA sequence from UCSC Genome Browser? ›

Click the entry for the gene in the RefSeq or Known Genes track, then click the Genomic Sequence link. Alternatively, you can click the DNA link in the top menu bar of the Genome Browser tracks window to access options for displaying the sequence.

What types of information can you retrieve from genome browsers? ›

Genome browsers are invaluable for viewing and interpreting the many different types of data that can be anchored to genomic positions. These include variation, transcription, the many types regulatory data such as methylation and transcription factor binding, and disease associations.

What is the best Genome Browser? ›

Genome Viewers/Editors – Three of the Best
  • Artemis. Artemis is a genome viewer available from Sanger Institute. ...
  • Apollo. Apollo genome viewer is another java based genome viewer and annotation tool. ...
  • The NCBI Genome Workbench. The NCBI Genome Workbench is far more than just a genome viewer.
Jul 28, 2016

Why are meganucleases not more widely used in genome editing? ›

Gene Editing

Homing endonucleases have not achieved widespread adoption as tools for genome engineering. One reason for this is that while many modified homing endonucleases with different DNA-binding specificities have been created, they lack the modular DNA-binding domain architecture found in ZF or TALE proteins.

What is the difference between human GRCh38 and GRCh37? ›

GRCh38: What's the Difference? Both, GRCh37 and GRCh38 are human genome assemblies by the Genome Reference Consortium (GRC). GRCh38 (also called “build 38”) was released four years after the GRCh37 release in 2009, so it can be viewed as a version with updated annotations to the earlier assembly.

What is the difference between GenBank and RefSeq sequences? ›

GenBank sequence records are owned by the original submitter and cannot be altered by a third party. RefSeq sequences are not part of the INSDC but are derived from INSDC sequences to provide non-redundant curated data representing our current knowledge of known genes.

What is the difference between GRCh37 and GRCh38? ›

GRCh38 is an improved representation of the human genome compared to GRCh37, where many gaps were closed, sequencing errors corrected and centromere sequences modelled. For the state-of-the-art of the human genome and its annotation, go to GRCh38.

Is RefSeq curated? ›

RefSeq transcript and protein records for a subset of organisms, primarily mammals, are curated by NCBI staff. Curation is an ongoing process and some records have not been reviewed yet; the curation status is indicated on the RefSeq record in the COMMENT block.

What is the difference between RNA seq and gro seq? ›

GRO-Seq is a derivative of RNA-Seq that aims to measure rates of transcript (instead of steady state RNA levels) by directly measuring nascent RNA production. Transcription is halted, nuclei are isolated, labeled nucleotides are added back, and transcription briefly restarted resulting in labeled RNA molecules.

How many genomes are in RefSeq? ›

The Reference Sequence (RefSeq) project at the National Center for Biotechnology Information (NCBI) contains nearly 200 000 bacterial and archaeal genomes and 150 million proteins with up-to-date annotation.

What are the 4 types of genome? ›

There are four main types of genome-wide repeat, called LINEs (long interspersed nuclear elements), SINEs (short interspersed nuclear elements), LTR (long terminal repeat) elements and DNA transposons. Examples of each type are seen in this short segment of the genome.

What is the biggest sequenced genome? ›

The Australian lungfish has the largest genome of any animal so far sequenced. Siegfried Schloissnig at the Research Institute of Molecular Pathology in Austria and his colleagues have found that the lungfish's genome is 43 billion base pairs long, which is around 14 times larger than the human genome.

What is the largest genome database? ›

All of Us Research Program Makes Nearly 250,000 Whole Genome Sequences Available to Advance Precision Medicine. All of Us genomic dataset is world's largest and most diverse dataset of its kind, paving the way to advance precision medicine.

What are pseudogenes in UCSC Genome Browser? ›

Here, pseudogenes are defined as genomic sequences that are similar to known genes but exhibit various inactivating disablements (e.g. premature stop codons or frameshifts) in their putative protein-coding regions and are flagged as either recently-processed or non-processed.

How do I find my SNP in Genome Browser? ›

This tutorial demonstrates how to find all the single nucleotide polymorphisms in a gene using the UCSC Genome Browser.
  1. Set up Genome Browser display to see your gene.
  2. Turn on the SNPs track to see SNPs in your gene.
  3. Get SNPs from the Table Browser.
  4. Load Table Browser results as a Custom Track.

What tool do we use from the UCSC genome browser? ›

The Genome Browser in the Cloud (GBiC) program is a convenient tool that automates the setup of a UCSC Genome Browser mirror.

How is genome data stored? ›

After a genome has been sequenced, assembled and annotated it needs to be shared in a format that is easily and freely accessible to all. This can be done via a database called a genome browser.

How many different genome browsers are there? ›

Three major genome browsers are freely accessible online — the University of California, Santa Cruz (UCSC) Genome Browser, the Wellcome Trust Sanger Institute (WTSI)/European Bioinformatics Institute (EBI) Ensembl browser and the National Center for Biotechnology Information (NCBI) MapViewer.

What is the most accurate genome sequencing? ›

Whole Genome Sequencing provides the most accurate and powerful look at DNA traits related to health, disease, fitness, and nutrition. Whole-genome sequencing (WGS) is by far the most powerful form of DNA sequencing available on the market.

What is the most widely used genome editing technology? ›

CRISPR/Cas9 is the most widely used genome editor and is a powerful tool for understanding gene function. Because CRISPR/Cas9 is an RNA-based system, it can be more efficiently and easily modified than the protein-based approaches and allows for targeting of multiple sites.

What is 1000 genome browser? ›

The 1000 Genome Browser is an interactive graphical viewer that allows users to explore variant calls, genotype calls and supporting evidence (such as aligned sequence reads) that have been produced by the 1000 Genomes Project.

What is the most controversial use of CRISPR? ›

DNA replacement in human embryos (germline genome therapy) The most controversial usage of CRISPR-Cas9 is the modification of human embryo DNA, or, in other words, its use for germline genome therapy.

What is the most advanced gene editing tool? ›

CRISPR/Cas9 – a specific, efficient and versatile gene-editing technology we can harness to modify, delete or correct precise regions of our DNA. Dr. Emmanuelle Charpentier, one of our scientific founders, co-invented CRISPR/Cas9 gene editing.

Is genome editing the same as CRISPR? ›

CRISPR-Cas9 was adapted from a naturally occurring genome editing system that bacteria use as an immune defense. When infected with viruses, bacteria capture small pieces of the viruses' DNA and insert them into their own DNA in a particular pattern to create segments known as CRISPR arrays.

Should I use hg19 or HG38? ›

Here, the improved reference genome (HG38) increased the number of SNVs identified from identical sequencing data, suggesting that genetic variants missed by using HG19 could be identified using HG38. Therefore, we again recommend the newer version (HG38) for sequencing data analysis aimed at variant calling.

Can you have two humans with exactly the same genome? ›

Theoretically, same-sex siblings could be created with the same selection of chromosomes, but the odds of this happening would be one in 246 or about 70 trillion. In fact, it's even less likely than that.

Are there 3 million differences between one person's genome and another person's genome? ›

Every person's genome is around 99.9% the same as everyone else's, but that 0.1% equates to around 3 million differences. Others can influence our susceptibility to develop a disease. We can now sequence and analyse genomic information to inform healthcare, helping to better diagnose, treat and even prevent disease.

What are three types of reference sequences? ›

Recommended Reference Sequences types are:
  • gene/genomic region - LRG_199.
  • coding transcript (or non-coding transcript) - LRG_199t1.
  • protein - LRG_199p1.

What are the two types of genome sequencing? ›

Two methods, whole exome sequencing and whole genome sequencing, are increasingly used in healthcare and research to identify genetic variations; both methods rely on new technologies that allow rapid sequencing of large amounts of DNA. These approaches are known as next-generation sequencing (or next-gen sequencing).

Which is better DNA or protein sequence database search? ›

Searches with protein sequences (BLASTP, FASTP, SSEARCH,) or translated DNA sequences (BLASTX, FASTX) are preferred because they are 5–10-fold more sensitive than DNA:DNA sequence comparison.

What is a scaffold vs contig genome? ›

A scaffold is a portion of the genome sequence reconstructed from end-sequenced whole-genome shotgun clones. Scaffolds are composed of contigs and gaps. A contig is a contiguous length of genomic sequence in which the order of bases is known to a high confidence level.

How is next generation sequencing different from GWAS? ›

GWAS is based on the common disease-common variant hypothesis, and could provide information on how common genetic variability confers risk for the common diseases (2). While for rare Mendelian disorders, NGS could pinpoint novel genes that contain mutations underlying the phenotype.

What is the difference between whole genome sequencing and metagenomics? ›

WGS aims to analyze the whole genome of a single bacterial colony, while amplicon-based marker gene sequencing (e.g., 16S/ITS) or shotgun metagenomics focuses on microbial communities within a sample, usually without culture [9,10].

What is the difference between Ensembl and RefSeq transcripts? ›

While Ensembl gene models are annotated directly on the reference genome, RefSeq annotates on mRNA sequences. Due to sequence differences between the reference genomes and individual mRNAs, some of the RefSeq mRNAs may not map perfectly to the reference genome.

Is RefSeq a protein database? ›

A comprehensive, integrated, non-redundant, well-annotated set of reference sequences including genomic, transcript, and protein.

Can you use trizol for RNA-Seq? ›

We do not recommend the use of Trizol alone for total RNA isolation, as the use of Trizol often results in samples that are contaminated by proteins and organics which can inhibit the library making process.

Is transcriptomics the same as RNA-Seq? ›

What is the difference between RNA-Seq and transcriptomics? Transcriptomics broadly refers to the study of RNA related to its expression levels, function, structure, and regulation. RNA-Seq is more specific and refers to the technique to study both the sequence and quantity of RNA.

What is the difference between Illumina and Nanopore RNA-Seq? ›

Illumina sequencers tend to be high accuracy with a read accuracy of >99.9% while Oxford Nanopore provides sequencers with a read accuracy of between 87% and 98%4. Of course, the cost usually plays an important role in any purchasing decision.

Does RefSeq only contain curated sequences? ›

The RefSeq collection includes complete or incomplete genome sequences, transcripts and proteins. Genomic sequence records are added when whole genome submissions are submitted to GenBank and are updated as those genome sequencing projects submit updates.

What are the five types of viral genomes? ›

Viral genomes exhibit extraordinary diversity with respect to nucleic acid type, size, complexity, and the information transfer pathways they follow. Thus, viral nucleic acids can be DNA or RNA, double-stranded or single-stranded, monopartite or multipartite, linear or circular, as short as 2 kb or up to 2500 kb long.

What is the gene name to RefSeq? ›

RefSeq Gene Fnip1

Description: Mus musculus folliculin interacting protein 1 (Fnip1), mRNA.

What is the use of Ensembl Genome Browser? ›

Ensembl provides a genome browser that acts as a single point of access to annotated genomes for mainly vertebrate species (Video 1 and Figure 2). Information about genes, transcripts and further annotation can be retrieved at the genome, gene and protein level.

What tool do we use from the UCSC Genome Browser? ›

The Genome Browser in the Cloud (GBiC) program is a convenient tool that automates the setup of a UCSC Genome Browser mirror.

What is the difference between NCBI RefSeq and Ensembl? ›

While Ensembl gene models are annotated directly on the reference genome, RefSeq annotates on mRNA sequences. Due to sequence differences between the reference genomes and individual mRNAs, some of the RefSeq mRNAs may not map perfectly to the reference genome.

What are tracks in UCSC Genome Browser? ›

Genome Browser annotation tracks are based on files in line-oriented format. Each line in the file defines a display characteristic for the track or defines a data item within the track. Annotation files contain three types of lines: browser lines, track lines, and data lines.

What kind of database is Ensembl? ›

Ensembl genome database project is a scientific project at the European Bioinformatics Institute, which provides a centralized resource for geneticists, molecular biologists and other researchers studying the genomes of our own species and other vertebrates and model organisms.

What are the primary steps of Ensembl genome browser? ›

Ensembl
  • A first look at our views.
  • Investigating a gene. Gene summary. Sequence. ...
  • Investigating a transcript (splice variant) Exons and introns. ...
  • Investigating a genomic region. Finding the location tab. ...
  • Investigating a sequence variation. Finding the variant tab. ...
  • Investigating gene regulation. Regulation in location views.

What is bigWig in UCSC Genome Browser? ›

The bigWig format is useful for dense, continuous data that will be displayed in the Genome Browser as a graph. BigWig files are created from wiggle (wig) type files using the program wigToBigWig . Alternatively, bigWig files can be created from bedGraph files, using the program bedGraphToBigWig .

What are the two main types of molecular databases in NCBI? ›

MMDB. NCBI has upgraded both the MMDB (Molecular Modeling Database) and GenBank sequence record tools so that they can process the complete set of Protein Data Bank (PDB) molecular structure data.

Is reference sequence the same as GenBank? ›

GenBank sequence records are owned by the original submitter and cannot be altered by a third party. RefSeq sequences are not part of the INSDC but are derived from INSDC sequences to provide non-redundant curated data representing our current knowledge of known genes.

What is the difference between NGS and RNA-Seq? ›

For read-counting methods, such as gene expression profiling, the digital nature of NGS allows a virtually unlimited dynamic range. RNA-Seq quantifies individual sequence reads aligned to a reference sequence, producing absolute rather than relative expression values.

Is UCSC Genome Browser 0 or 1 based? ›

The UCSC genome browser uses both systems and refer to the base coordinate system as “one-based, fully-closed” (used in the UCSC genome browser display) and interbase coordinate system as “zero-based, half-open” (used in their tools and file formats).

What do the arrows on the Genome Browser mean? ›

In full display mode, arrowheads on the connecting intron lines indicate the direction of transcription. In situations where no intron is visible (e.g. single-exon genes, extremely zoomed-in displays), the arrowheads are displayed on the exon block itself.

References

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