cytoBand Chromosome Band bed 4 + Chromosome Bands Localized by FISH Mapping Clones 1 1 0 0 0 150 50 50 0 0 0

Description

\

The chromosome band track represents the approximate \ location of bands seen on Giemsa-stained chromosomes at\ an 800 band resolution.

\

Methods

\

A full description of the method by which the chromosome \ band locations are estimated can be found in \ Furey, T.S., and Haussler, D.,Integration of the Cytogenetic Map with the\ Draft Human Genome Sequence, Hum. Mol. Gen., 12(9):1037-1044 (2003).\

\ \

Barbara Trask, Vivian Cheung, Norma Nowak and others in the BAC Resource\ Consortium used fluorescent in-situ\ hybridization (FISH) to determine a cytogenetic location for \ large genomic clones on the chromosomes.\ The results from these experiments are the primary source of information used\ in estimating the chromosome band locations.\ For more information about the BAC Resource Consortium, see "Integration of cytogenetic landmarks into the draft sequence of\ the human genome", Nature, 409:953-958, Feb. 2001 and the accompanying web site\ Human BAC Resource.\

\ \

\ BAC clone placements in the human sequence are determined at UCSC using a combination of full BAC clone sequence,\ BAC end sequence, and STS marker information.\

\

Credits

\

We would like to thank all of the labs that have contributed to this resource:\

\ map 1 mapGenethon STS Markers bed 5 + Various STS Markers 1 2 0 0 0 127 127 127 0 0 0 map 1 stsMap STS Markers bed 5 + STS Markers on Genetic (blue) and Radiation Hybrid (black) Maps 1 4 0 0 0 128 128 255 0 0 0

Description

\

This track shows locations of Sequence Tagged Site (STS) markers\ along the draft assembly. These markers have been mapped using \ either genetic mapping (Genethon, Marshfield, and deCODE maps),\ radiation hybridization mapping (Stanford, Whitehead RH, and GeneMap99 maps) or\ YAC mapping (the Whitehead YAC map) techniques. \ Prior to August 2001, this track also\ showed the approximate position of fluorescent in situ hybridization (FISH) mapped clones.\ In the August 2001 and later assemblies, the FISH clones are displayed in a separate track.

\

Genetic map markers are shown in blue; radiation hybrid map markers are shown \ in black. When a marker maps to multiple positions in the genome, it's shown in a \ lighter color.

\ \

Using the Filter

\

The track filter can be used to change the color or include/exclude a set of map data \ within the track. This is helpful when many items are shown in the track\ display, especially when only some are relevant to the current task. To use the\ filter:\

\

When you have finished configuring the filter, click the Submit button.

\ \

Credits

\

Many thanks to the researchers who worked on these\ maps, and to Greg Schuler, Arek Kasprzyk, Wonhee Jang,\ Terry Furey and Sanja Rogic for helping\ process the data. Additional data on the individual maps can be\ found at the following links:\

\

\ \ map 1 fishClones FISH Clones bed 5 + Clones Placed on Cytogenetic Map Using FISH 0 6 0 150 0 127 202 127 0 0 0

Description

\

This track shows the location of fluorescent in situ hybridization (FISH) mapped clones along the \ draft assembly sequence. The locations of these clones were\ contributed as a part of The BAC Resource Consortium's paper "\ Integration of cytogenetic landmarks into the draft sequence of the\ human genome", Nature 409:953-958, Feb. 2001.

\ \

More information about the BAC clones, including how they can be\ obtained, can be found at the \ Human BAC Resource\ and the Clone Registry\ web sites hosted by NCBI.\ To view Clone Registry information for a clone, click on the clone name at the top of the details page for that item.

\ \

Using the Filter

\

The track filter can be used to change the color or include/exclude the display of a dataset from an individual lab. This is helpful when many items are shown in the track\ display, especially when only some are relevant to the current task. To use the\ filter:\

\

When you have finished configuring the filter, click the Submit button.

\ \

Credits

\

We would like to thank all of the labs that have contributed to this resource:\

\ \ \ map 1 genMapDb GenMapDB Clones bed 6 + GenMapDB BAC Clones 0 7 0 0 0 127 127 127 0 0 0

Description

\

BAC clones from GenMapDB\ are placed on the draft sequence using BAC end sequence information\ and confirmed using STS markers by Vivian Cheung's lab at the\ Department of Pediatrics, University of Pennsylvania. Further\ information about each clone can be obtained by clicking on the clone\ name on the track detail page.\

Credits

\ Thanks to Vivian Cheung's lab \ and GenMapDB at the University of Pennsylvania for providing the data used to create this track.\ map 1 recombRate Recomb Rate bed 4 + Recombination Rate from deCODE, Marshfield, or Genethon Maps (deCODE default) 0 8 0 0 0 127 127 127 0 0 0

Description

\

The recombination rate track represents\ calculated sex-averaged rates of recombination based on either the\ deCODE, Marshfield, or Genethon genetic maps. By default, the deCODE\ map rates are displayed. Female and male specific recombination\ rates, and well as rates from the Marshfield and Genethon maps, can\ also be displayed by choosing the appropriate filter option on the track description page.\

\ \

Methods

\

The deCODE genetic map was created at \ deCODE Genetics and is \ based on 5,136 microsatellite markers for 146 families with a total\ of 1,257 meiotic events. For more information on this map, see\ A. Kong et. al., "A high-resolution recombination map of the human genome", \ Nature Genetics, 31(3), pages 241-247 (2002).\

\

The Marshfield genetic map was created at the Center\ for Medical Genetics and is based on 8,325 short tandem repeat\ polymorphisms (STRPs) for 8 CEPH families consisting of 134\ individuals with 186 meioses. For more information on this map,\ see K.W. Broman et. al.,\ "Comprehensive\ Human Genetic Maps: Individual and Sex-Specific Variation in\ Recombination", American Journal of Human Genetics\ 63:861-689 (1998).\

\

The Genethon genetic map was created at Genethon and is\ based on 5,264 microsatellites for 8 CEPH families consisting of 134\ individuals with 186 meioses. For more information on this map,\ see Dib et. al., "A Comprehensive Genetic Map of the Human Genome\ Based on 5,264 Microsatellites", Nature, 380, pages 152-154\ (1996).\

\

Each base is assigned the recombination rate calculated by\ assuming a linear genetic distance across the immediately flanking\ genetic markers. The recombination rate assigned to each 1Mb window\ is the average recombination rate of the bases contained within the\ window.\

\ \

Using the Filter

\

To view a particular map or gender-specific rate, select the corresponding\ option from the "Map Distances" pulldown list. By default, the browser \ displays the deCODE sex-averaged distances.

\ \

Credits

\

This track is produced at UCSC and uses data that are freely available for\ the Genethon, Marshfield, and deCODE genetic maps (see above links). Thanks\ to all who have played a part in the creation of these maps.

\ \ map 1 ctgPos Map Contigs Physical Map Contigs 0 9 150 0 0 202 127 127 0 0 0

Description

\ This track shows the locations of contigs of clones\ on the physical map. \ \

Method

\ In assembly versions prior to the August 2001\ freeze, this track was based on the Washington University accession\ map, which in turn was based on a fingerprint contig (FPC) map\ described in "A physical map of the human genome", Nature 409: 934-941. \

\

\ Starting with the August 2001 freeze, this track is based on tiling path (TPF) \ maps curated by the sequencing centers responsible for each chromosome. Imre\ Vastrik at the European Bioinformatics Institute merges the TPF\ maps with the FPC map, favoring the TPF map where there are conflicts.\ This step increases the clone coverage substantially over that in\ the TPF maps. This merged map is then used as the basis for the\ human genome assembly. The clone contigs in this merged map are shown in\ this track.\

\ map 0 gold Assembly bed 3 + Assembly from Fragments 0 10 150 100 30 230 170 40 0 0 0

Description

\

This track shows the draft assembly of the $organism genome.\ This assembly merges contigs from overlapping drafts and\ finished clones into longer sequence contigs. The sequence\ contigs are ordered and oriented when possible by mRNA, EST,\ paired plasmid reads (from the SNP Consortium) and BAC end\ sequence pairs.

\

In dense mode, this track depicts the path through the draft and \ finished clones (aka the golden path) used to create the assembled sequence. \ Clone boundaries are distinguished by the use of alternating gold and brown \ coloration. Where gaps\ exist in the path, spaces are shown between the gold and brown\ blocks. If the relative order and orientation of the contigs\ between the two blocks is known, a line is drawn to bridge the\ blocks.

\

\ Clone Type Key:\

\ \ map 1 gap Gap bed 3 + Gap Locations 1 11 0 0 0 127 127 127 0 0 0

Description

\ This track depicts gaps in the assembly. These gaps - with the\ exception of intractable heterochromatic gaps - will be closed during the\ finishing process. \

\ Gaps are represented as black boxes in this track.\ If the relative order and orientation of the contigs on either side\ of the gap is known, it is a bridged gap and a white line is drawn \ through the black box representing the gap. \

\

There are four principal types of gaps:\

\ map 1 clonePos Coverage Clone Coverage/Fragment Position 0 14 0 0 0 180 180 180 0 0 0

Description

\

\ In dense display mode, this track shows the coverage level of \ the genome. Finished regions are depicted in black. Draft regions \ are shown in various shades of gray that correspond to the level of coverage. \

\ In full display mode, this track shows the position of each contig inside each \ draft or finished clone ("fragment") in the assembly. For some \ assemblies, clones in the sequencing center tiling path are displayed with\ blue rather than gray backgrounds.\

\ map 0 bacEndPairs BAC End Pairs bed 6 + BAC End Pairs 0 15 0 0 0 127 127 127 0 0 0

Description

\

Bacterial artificial chromosomes (BACs) are a key part of many large\ scale sequencing projects. A BAC typically consists of 50-300kb of\ DNA. During the early phase of a sequencing project, it is common\ to sequence a single read (approximately 500 bases) off each end of\ a large number of BACs. Later on in the project, these BAC end reads\ can be mapped to the genome sequence. \

\

This track shows these mappings\ in cases where both ends could be mapped. These BAC end pairs can\ be useful for validating the assembly over relatively long ranges. In some\ cases, the BACs are useful biological reagents. This track can also be\ used for determining which BAC contains a given gene, useful information\ for certain wet lab experiments.\ \

A valid pair of BAC end sequences must be\ at least 50Kb but no more than 600Kb away from each other. \ The orientation of the first BAC end sequence must be "+" and\ the orientation of the second BAC end sequence must be "-".

\ \

Methods

\

BAC end sequences are placed on the assembled sequence using\ Jim Kent's \ blat \ program.

\ \

Credits

\

Additional information about the clone, including how it\ can be obtained, may be found at the \ NCBI Clone Registry.\ To view the registry entry for a specific clone, open the details page for the clone and click on its name at the top of the page.\

\ map 1 gcPercent GC Percent bed 4 + Percentage GC in 20,000 Base Windows 0 23 0 0 0 127 127 127 1 0 0

Description

\

\ The GC percent track shows the percentage of G (guanine) and C (cytosine) bases in\ a 20,000 base window. Windows with high GC content are drawn more darkly than windows\ with low GC content. High GC content is typically associated with gene rich areas.\

\

Credits

\

\ This track was generated at UCSC.\ map 1 genomicSuperDups Segmental Dups bed 6 Duplications of >1000 Bases of Non-RepeatMasked Sequence 0 27 0 0 0 127 127 127 0 0 0

Description

\ \

This region was detected as a putative genomic duplication within the golden path.\ Orange, yellow, dark-light gray represent similarities of >99\\%, 99-98\\% and 98-90% \ respectively. Duplications greater than 98% similarity that lack sufficient SDD \ evidence (likely missed overlaps) are shown as red. Cut off values were at least \ 1 kb of total sequence aligned (containing at least 500 bp non-RepeatMasked sequence) \ and at least 90% sequence identity. \ \

Methods

\ For a description of the 'fuguization' detection method see Bailey, JA, et. al., \ (2001). "Segmental duplications: organization and impact within the current human genome project assembly."\ Genome Res 11:1005-17. \ \

Credits

\ The data were provided by Jeff Bailey and \ Evan Eichler.\

\ varRep 1 knownGene Known Genes genePred refPep refMrna Known Genes Based on SWISS-PROT, TrEMBL, mRNA, and RefSeq 3 34 12 12 120 133 133 187 0 0 0

Description

\

\ The Known Genes track shows known protein coding genes based on \ proteins from SWISS-PROT, TrEMBL, and TrEMBL-NEW and their\ corresponding mRNAs from Genbank.\ Coding exons are displayed \ taller than 5' and 3' untranslated regions (UTR). Connecting introns \ are one-pixel lines with hatch marks indicating direction of transcription.\ Entries which have corresponding entries in PDB are colored black.\ Entries which either have corresponding proteins in SWISS-PROT or mRNAs that are \ NCBI Reference Sequences with a "Reviewed" status are colored dark blue.\ Entries which have mRNAs that are \ NCBI Reference Sequences with a "Provisional" status are colored lighter blue.\ Everything else is colored with lightest blue.

\ \

Method

\

\ All mRNAs of a species are aligned against the genome using the blat\ program. When a single mRNA aligns in multiple places, only\ the best alignments are kept. The alignments must also have \ at least 98% sequence identity to be kept. \ This set of mRNA alignments is further reduced by keeping only those mRNAs that \ are referenced by a protein in SWISS-PROT, TrEMBL, or TrEMBL-NEW.

\

\ Among multiple mRNAs referenced by a single protein, the best mRNA is chosen based on \ a quality score, which depends on its length, how good its translation matches \ the protein sequence, and its release date.\ The list of mRNA and protein pairs are further cleaned up by removing \ short invalid entries and consolidating entries with identical CDS regions.

\

\ Finally, RefSeq entries which are derived from DNA sequences instead of \ mRNA sequences are added. Disease annotations are from SWISS-PROT.

\ \

Credits

\

\ The Known Genes track is produced at UCSC based primarily on cross-references \ between proteins from \ SWISS-PROT \ (also including TrEMBL and TrEMBL-NEW) and mRNAs from Genbank\ generated by scientists worldwide. Part of \ NCBI RefSeq \ data are also included in this track.

\ \

Data Use Restrictions

\

\ The SWISS-PROT entries in this annotation track are copyrighted. They are \ produced through a collaboration \ between the Swiss Institute of Bioinformatics and the EMBL Outstation - the \ European Bioinformatics Institute. There are no restrictions on their use by \ non-profit institutions as long as their content is in no way modified and this \ statement is not removed. Usage by and for commercial entities requires a \ license agreement (see \ http://www.isb-sib.ch/announce/ or send an email to \ license@isb-sib.ch).

\ \ genes 1 refGene RefSeq Genes genePred refPep refMrna RefSeq Genes 0 35 12 12 120 133 133 187 0 0 0

Description

\

\ The RefSeq Genes track shows known protein coding genes taken from mRNA \ reference sequences compiled at LocusLink. Coding exons are represented by \ blocks connected by horizontal lines representing introns. The 5' and 3' \ untranslated regions (UTRs) are displayed as shorter blocks on the leading \ and trailing ends of the aligning regions. In full display mode, arrowheads \ on the connecting intron lines indicate the direction of transcription.\

\

\ Non-coding RNA genes have their own track in some assemblies.\

\

Method

\

\ Refseq mRNAs are aligned against the genome using the blat\ program. When a single mRNA aligns in multiple places, only\ the best alignments which also have at least 98% sequence identity are kept.\

\

Using the Filter

\

The track filter can be used to configure the labeling of the features within\ the track. By default, items are labeled by gene name. Click the \ appropriate Label option to display the accession name instead of the gene\ name, show both the gene and accession names, or turn off the label completely.\ After you have made your selection, click Submit to return to the tracks display\ page.\

Credits

\

\ The RefSeq Genes track is produced at UCSC from mRNA sequence data\ generated by scientists worldwide and curated by the \ NCBI RefSeq project. \

\ genes 1 sanger22 Sanger 22 genePred Sanger Institute Chromosome 22 Genes 3 37.3 0 100 180 127 177 217 0 0 1 chr22,

Description

\

\ This track contains curated annotations of chromosome 22 produced by the\ Chromosome \ 22 Group at the Sanger Institute. They are described in the \ paper Collins, J.E., Goward, M.E., Cole, C.G., Smink, L.J., Huckle, E.J., \ Knowles, S., Bye, J.M., Beare, D.M. & Dunham I. (2003) \ Reevaluating Human Gene Annotation: A Second Generation \ Analysis of Human Chromosome 22. Genome Res. 13(1):27-36.\

\ Over 10% of the human genome, including two complete\ chromosomes -- 20\ and 22 --\ have been annotated by the Sanger Institute Sequence\ Annotation Team in collaboration with the individual \ Chromosome \ Project Teams. \

\ NOTE: Sanger22 annotations appear only on chromosome 22 in the Genome Browser.\ \

Methods

\

\ Finished genomic sequence is analysed on a clone by clone basis using a\ combination of similarity searches against DNA and protein databases as\ well as a series of ab initio gene predictions (GENSCAN, FGENESH). Gene\ structures are annotated on the basis of human interpretation of the\ combined supportive evidence generated during sequence analysis. In\ parallel, experimental methods are applied to extend incomplete\ gene structures and discover new genes. The latter is initiated by\ comparative analysis of the finished sequence with vertebrate datasets\ such as the Riken mouse cDNAs, mouse whole-genome shotgun data and\ GenescopeTetraodon Ecores.

\ \

Credits

\

\ These annotations were obtained from the\ Internet at http://www.sanger.ac.uk/HGP/Chr22. \ Thanks to the Sanger Institute for providing this data set. Email inquiries\ may be sent to humquery@sanger.ac.uk.\ genes 1 sanger22pseudo Sanger 22 Pseudo genePred Sanger Center Chromosome 22 Pseudogenes 0 37.4 30 130 210 142 192 232 0 0 1 chr22,

Description

\

\ This track contains curated annotations of chromosome 22 produced by the\ Chromosome \ 22 Group at the Sanger Institute. They are described in the \ paper Collins, J.E., Goward, M.E., Cole, C.G., Smink, L.J., Huckle, E.J., \ Knowles, S., Bye, J.M., Beare, D.M. & Dunham I. (2003) \ Reevaluating Human Gene Annotation: A Second Generation \ Analysis of Human Chromosome 22. Genome Res. 13(1):27-36.\

\ Over 10% of the human genome, including two complete\ chromosomes -- 20\ and 22 --\ have been annotated by the Sanger Institute Sequence\ Annotation Team in collaboration with the individual \ Chromosome \ Project Teams. \

\ NOTE: Sanger22 annotations appear only on chromosome 22 in the Genome Browser.\ \

Methods

\

\ Finished genomic sequence is analysed on a clone by clone basis using a\ combination of similarity searches against DNA and protein databases as\ well as a series of ab initio gene predictions (GENSCAN, FGENESH). Gene\ structures are annotated on the basis of human interpretation of the\ combined supportive evidence generated during sequence analysis. In\ parallel, experimental methods are applied to extend incomplete\ gene structures and discover new genes. The latter is initiated by\ comparative analysis of the finished sequence with vertebrate datasets\ such as the Riken mouse cDNAs, mouse whole-genome shotgun data and\ GenescopeTetraodon Ecores.

\ \

Credits

\

\ These annotations were obtained from the\ Internet at http://www.sanger.ac.uk/HGP/Chr22. \ Thanks to the Sanger Institute for providing this data set. Email inquiries\ may be sent to humquery@sanger.ac.uk.\ genes 1 ensGene Ensembl Genes genePred ensPep Ensembl Gene Predictions 1 40 150 0 0 202 127 127 0 0 0 http://www.ensembl.org/perl/transview?transcript=$$

Description

\

\ These gene predictions are from Ensembl.

\ \

Methods

\

For a description of the methods used in Ensembl gene prediction, refer to \ "\ The Ensembl genome database project", Nucleic Acids Research, \ 2002, 30(1) 38-41.

\ \

Credits

\

\ Thanks to Ensembl for providing this annotation.

\ \ genes 1 acembly Acembly Genes genePred acemblyPep acemblyMrna Acembly Gene Predictions With Alt-Splicing 1 41 155 0 125 205 127 190 0 0 0 http://www.ncbi.nih.gov/IEB/Research/Acembly/av.cgi?db=human&l=$$

Description

\

This track shows gene models reconstructed solely from\ mRNA and EST evidence by Danielle and Jean Thierry-Mieg\ and Vahan Simonyan using the Acembly program.

\ \

Methods

\

Acembly attempts to find the best alignment of each mRNA against the \ genome, and considers alternative splice models. If more than one gene \ model is produced that has statistical significance, all of these models \ are displayed.

\ \

Credits

\

Thanks to Jean Thierry-Mieg at NIH for \ providing this track.

\ \ \ genes 1 twinscan Twinscan genePred twinscanPep Twinscan Gene Predictions Using Mouse/Human Homology 0 45 0 100 100 127 177 177 0 0 0

Description

\

\ The Twinscan program predicts genes in a manner similar to Genscan, except that\ Twinscan takes advantage of genome comparison to improve gene prediction\ accuracy. More information and a web server can be found at\ \ http://genes.cs.wustl.edu/.\

\

Methods

\

\ The Twinscan algorithm is described in Korf I, Flicek P, Duan D, and Brent MR \ (2001), "Integrating genomic homology into gene structure prediction", \ Bioinformatics 17:S140-148.\

\

Credits

\

\ Thanks to Michael Brent's Computational Genomics Group at Washington University St. Louis for providing these data.\ genes 1 slamMouse Slam Mouse genePred Slam Gene Predictions Using Human/Mouse Homology 0 45.5 100 50 0 175 150 128 0 0 0

Description and Credits

\ \

\ Slam predicts coding exons and conserved noncoding regions in a pair of homologous DNA sequences, incorporating both statistical sequence properties and degree of conservation in making the predictions. This particular annotation uses the Feb. 2002 (mm2) assembly of the mouse genome. The model is symmetric and the same gene structure (with possibly different exon lengths) is predicted in both sequences. \ \

\ The symmetry of the model gives it a higher degree of accuracy for regions where the true underlying gene structures contain the same number of coding exons, in cases where this is not true, or when one of the sequences is of lower quality and contains in-frame stop codons, the resulting predictions tend to have lower accuracy.\ \

\ More information on the accuracy of the predictions can be found at http://bio.math.berkeley.edu/slam/mouse. A web server for individual requests is available at http://bio.math.berkeley.edu/slam.\

\

References

\ M. Alexandersson, S. Cawley, L. Pachter (2003). SLAM - Cross-species Gene Finding and Alignment with a Generalized Pair Hidden Markov Model. Genome Research 13(3):496-502.\

L. Pachter, M. Alexandersson, S. Cawley (2001). \ Applications of Generalized Pair Hidden Markov Models to Alignment and Gene Finding Problems, \ Proceedings of the Fifth Annual International Conference on Computational Molecular Biology (RECOMB 2001).\

L. Pachter , M. Alexandersson, S. Cawley (2002). \ Applications of Generalized Pair Hidden Markov Models to Alignment and Gene Finding Problems, \ Journal of Computational Biology 9(2):389-400.\ genes 1 sgpGene SGP Genes genePred sgpPep SGP Gene Predictions Using Mouse/Human Homology 0 47 0 90 100 127 172 177 0 0 0

Description

\

\ This track shows gene predictions from the SGP program, which is being developed at \ the Grup de Recerca en\ Informàtica Biomèdica (GRIB) at Institut Municipal d'Investigació Mèdica (IMIM) in \ Barcelona. To predict genes in a genomic\ query, SGP combines geneid predictions with tblastx comparisons of the genomic query against other genomic sequences.\

\

Credits

\

\ Thanks to GRIB for providing these gene predictions.\

\ \ \ \ genes 1 softberryGene Fgenesh++ Genes genePred softberryPep Fgenesh++ Gene Predictions 0 48 0 100 0 127 177 127 0 0 0

Description

\

Fgenesh++ predictions are based on Softberry's gene finding software.

\ \

Methods

\ Fgenesh++ uses both hidden Markov models (HMMs) and protein similarity to find genes in a completely \ automated manner. For more information, see the paper Solovyev VV (2001), \ "Statistical approaches in Eukaryotic gene prediction" in the Handbook of \ Statistical Genetics (ed. Balding D. et al.), John Wiley & Sons, Ltd., p. 83-127.\ \

Credits

\

The Fgenesh++ gene predictions were produced by \ Softberry Inc. \ Commercial use of these predictions is restricted to viewing in \ this browser. Please contact Softberry Inc. to make arrangements for further commercial access.\ \ genes 1 geneid Geneid Genes genePred geneidPep Geneid Gene Predictions 0 49 0 90 100 127 172 177 0 0 0

Description

\

\ This track shows gene predictions from the geneid program developed at the \ Grup de Recerca en\ Informàtica Biomèdica (GRIB) at Institut Municipal d'Investigació Mèdica (IMIM) in \ Barcelona. \

\

Methods

\

\ Geneid is a program to predict genes in anonymous genomic sequences designed \ with a hierarchical structure. In the first step, splice sites, start and stop \ codons are predicted and scored along the sequence using Position Weight Arrays \ (PWAs). Next, exons are built from the sites. Exons are scored as the sum of the \ scores of the defining sites, plus the the log-likelihood ratio of a \ Markov Model for coding DNA. Finally, from the set of predicted exons, the gene \ structure is assembled, maximizing the sum of the scores of the assembled exons. \

\

Credits

\

\ Thanks to GRIB for providing these data.\

\ genes 1 genscan Genscan Genes genePred genscanPep Genscan Gene Predictions 1 50 170 100 0 212 177 127 0 0 0

Description

\

This track shows predictions from the \ Genscan program written by Chris Burge.\

\

Methods

\ For a description of the Genscan program and the model that underlies it, refer\ to Burge C and Karlin S (1997), \ " \ Prediction of Complete Gene Structures in Human Genomic DNA", \ J. Mol. Biol. 268, 78-94. The splice site models used are described in \ more detail in Burge C (1998), "Modeling Dependencies in Pre-mRNA Splicing \ Signals" in Salzberg S, Searls D, and Kasif S, eds. \ \ Computational Methods in Molecular Biology, Elsevier Science, Amsterdam, \ 127-163. \ \

Credits

\ Thanks to Chris Burge for providing these data.\ genes 1 rnaGene RNA Genes bed 6 + Non-coding RNA Genes (dark) and Pseudogenes (light) 0 52 170 80 0 230 180 130 0 0 1 chr7,

Description

\ This track shows the location of non-protein coding RNA genes and\ pseudo-genes. \

\ Feature types include:\

\ \

Methods

\ \

Eddy-tRNAscanSE (tRNA genes, Sean Eddy):

\ tRNAscan-SE 1.23 with default parameters.\ Score field contains tRNAscan-SE bit score; >20 is good, >50 is great.\ \

Eddy-BLAST-tRNAlib (tRNA pseudogenes, Sean Eddy):

\ WUBLAST 2.0, with options "-kap wordmask=seg B=50000 W=8 cpus=1".\ Score field contains % identity in BLAST-aligned region.\ Used each of 602 tRNAs and pseudogenes predicted by tRNAscan-SE\ in the human oo27 assembly as queries. Kept all nonoverlapping\ regions that hit one or more of these with P <= 0.001. \ \

Eddy-BLAST-snornalib (known snoRNAs and snoRNA pseudogenes, Steve Johnson):

\ WUBLASTN 2.0, with options "-V=25 -hspmax=5000 -kap wordmask=seg \ B=5000 W=8 cpus=1".\ Score field contains BLAST score.\ Used each of 104 unique snoRNAs in snorna.lib as a query.\ Any hit >=95% full length and >=90% identity is annotated as a\ "true gene".\ Any other hit with P <= 0.001 is annotated as a "related sequence" \ and interpreted as a putative pseudogene.\ \

Eddy-BLAST-otherrnalib \ (non-tRNA, non-snoRNA noncoding RNAs with Genbank entries\ for the human gene.):

\ WUBLASTN 2.0 [15 Apr 2002]\ with options: "-kap -cpus=1 -wordmask=seg -W=8 -E=0.01 -hspmax=0\ -B=50000 -Z=3000000000". Exceptions to this are:\ \ The score field contains the BLASTN score. \ Used 41 unique miRNAs, and 29 other ncRNAs as queries.\ Any hit >=95% full length and >=95% identity is annotated as a \ "true gene".\ Any other hit with P <= 0.001 and >= 65% identity is annotated\ as a "related sequence". An exception to this is: all miRNAs consist \ \ of 16-26 bp sequences in Genbank \ and are only annotated if 100% full length and 100% identity. \ miRNAs consist of Let-7 from Pasquinelli et al., \ Nature (2000) 408:86; 40 from Mourelatos et al., Gene & Dev (2002) \ 16:720. \

Credits

\ These data were kindly provided by Sean Eddy at Washington University.\ genes 1 superfamily Superfamily bed 4 + Superfamily/SCOP: Proteins Having Homologs with Known Structure/Function 1 53 150 0 0 202 127 127 0 0 0 http://supfam.org/SUPERFAMILY/cgi-bin/gene.cgi?seqid=$$

Description

\

\ The \ Superfamily \ track shows proteins having homologs with known structures or functions.

\

\ Each entry on the track shows the coding region of a gene (based on Ensembl gene predictions).\ In full display mode, the label for an entry consists of the names of \ all known protein domains coded by this gene. This \ usually contains structural and/or function descriptions that provide valuable information to help users get a quick grasp of the biological significance of the gene.

\

Method

\

\ Data are downloaded from the Superfamily server.\ Using the cross-reference between Superfamily entries and Ensembl gene prediction entries\ and their alignment to the appropriate genome, the associated data are processed to generate \ a simple BED format track.

\

Credits

\

\ Superfamily is developed by\ Julian\ Gough at the MRC Laboratory\ of Molecular Biology, Cambridge.

\

\ Gough, J., Karplus, K., Hughey, R. and\ Chothia, C. (2001). "Assignment of Homology to Genome Sequences using a\ Library of Hidden Markov Models that Represent all Proteins of Known Structure". \ J. Mol. Biol., 313(4), 903-919.

\ \ genes 1 mrna $Organism mRNAs psl . $Organism mRNAs from Genbank 3 54 0 0 0 127 127 127 1 0 0

Description

\

\ The $Organism mRNA track shows alignments between $organism mRNAs\ in Genbank and the genome. Aligning regions (usually exons)\ are shown as black boxes connected by lines for gaps (spliced\ out introns usually). In full display, arrows on the introns\ indicate the direction of transcription.

\

Method

\

\ Genbank $organism mRNAs are aligned against the genome using the \ blat\ program. When a single mRNA aligns in multiple places, \ the alignment having the highest base identity is found. \ Only alignments that have a base identity level within 1% of\ the best are kept. Alignments must also have at least 95%\ base identity to be kept.

\ \

Using the Filter

\

The track filter can be used to change the color or include/exclude a subset of individual \ items within a track. This is helpful when many items are shown in the track\ display, especially when only some are relevant to the current task. To use the\ filter:\

    \
  1. Enter a value in one or more of the text boxes to filter the mRNA display. For\ example, to apply the filter to all liver mRNAs, type "liver" in the \ tissue box. For a list of permissible filter values, consult the non-positional table in\ the Table Browser that corresponds to the factor on which you wish to filter. For\ example, the non-positional table "tissue" contains all of the types of tissues\ that can be entered into the tissue text box. Wildcards can also be used in the\ filter.\
  2. If filtering on more than one value, choose the desired combination\ logic. If "and" is selected, only mRNAs that match all of the filter criteria will\ be highlighted. If "or" is selected, mRNAs that match any 1 of the filter criteria\ will be highlighted.\
  3. Choose the color or display characteristic that will be used to highlight or\ include/exclude the filtered items. If "exclude" is chosen, the browser will not \ display mRNAs that match the filter criteria. If "include" is selected, the browser \ will display only those mRNAs that match the filter criteria.\

\

\ When you have finished configuring the filter, click the Submit button.

\ \

Credits

\

\ The $Organism mRNA track is produced at UCSC from mRNA sequence data\ submitted to the international public sequence databases by \ scientists worldwide.

\ rna 1 intronGap 30\ intronEst Spliced ESTs psl est $Organism ESTs That Have Been Spliced 1 56 0 0 0 127 127 127 1 0 0

Description

\

The Spliced EST track displays Expressed Sequence Tags \ (ESTs) from Genbank that show signs of splicing when\ aligned against the genome. By requiring splicing, the level \ of contamination in the EST databases is drastically reduced\ at the expense of eliminating many genuine 3' ESTs.\ For a display of all ESTs (including unspliced), see the \ $Organism EST track.

\ \

Expressed sequence tags are single read (typically\ approximately 500 base) sequences which usually\ represent fragments of transcribed genes. Aligning \ regions (usually exons) are shown as black boxes \ connected by lines for gaps (usually spliced out introns). \ In full display mode, arrows on the introns\ indicate the direction of transcription. In the\ December 2001 assembly and later, this direction is\ taken by looking at the splice sites. In previous\ assemblies, the direction of transcription was taken from \ the Genbank annotations, which frequently were inaccurate.

\ \

Strand information provided for ESTs (+/-) indicates the\ direction of the match between the EST and the matching\ genomic sequence. It bears no relationship to the direction\ of transcription of the RNA with which it might be associated.\ \

Method

\

To make an EST, RNA is isolated from cells and reverse\ transcribed into cDNA. Typically, the cDNA is cloned\ into a plasmid vector, and a read taken from the 5'\ and/or 3' primer. For most - but not all - ESTs, the\ reverse transcription is primed by an oligo-dT, which\ hybridizes with the poly-A tail of mature mRNA. The\ reverse transcriptase may or may not make it to the 5'\ end of the mRNA, which may or may not be degraded.

\ \

In general, the 3' ESTs mark the end of transcription\ reasonably well, but the 5' ESTs may end at any point\ within the transcript. Some of the newer cap-selected\ libraries are starting to hit transcription start\ reasonably well. Before the cap-selection techniques\ emerged, some projects used random rather than poly-A\ priming in an attempt to get sequence distant from the\ 3' end. These projects were successful at this, but as\ a side effect also deposited sequences from unprocessed\ mRNA and perhaps even genomic sequences into the EST databases.\ (Even outside of the random-primed projects, there is a\ degree of non-mRNA contamination.) Because of this, a\ single unspliced EST should be viewed with considerable\ skepticism. However, because the $organism 3' UTRs are quite\ long, the splicing requirement does eliminate many genuine 3'\ ESTs.

\ \

To generate this track, $organism ESTs from Genbank are aligned \ against the genome using the \ blat program. Note that the maximum intron length\ allowed by blat is 500,000 bases, which may eliminate some ESTs with very \ long introns that might otherwise align. When a single \ EST aligns in multiple places, the alignment having the \ highest base identity is found. Only alignments that have \ a base identity level within 0.1% of the best are kept. \ Alignments must also have at least 98% base identity to be kept.

\ \

Using the Filter

\

The track filter can be used to change the color or include/exclude a subset of \ individual items within a track. This is helpful when many items are shown in the \ track display, especially when only some are relevant to the current task. To use the\ filter:\

    \
  1. Enter a value in one or more of the text boxes to filter the EST display. For\ example, to apply the filter to all ESTs expressed in the liver, type "liver" in the \ tissue box. For a list of permissible filter values, consult the non-positional table in\ the Table Browser that corresponds to the factor on which you wish to filter. For\ example, the non-positional table "tissue" contains all of the types of tissues\ that can be entered into the tissue text box. Wildcards can also be used in the\ filter.\
  2. If filtering on more than one value, choose the desired combination\ logic. If "and" is selected, only ESTs that match all of the filter criteria will\ be highlighted. If "or" is selected, ESTs that match any 1 of the filter criteria\ will be highlighted.\
  3. Choose the color or display characteristic that should be used to highlight or\ include/exclude the filtered items. If "exclude" is chosen, the browser will not \ display ESTs that match the filter criteria. If "include" is selected, the browser \ will display only those ESTs that match the filter criteria.\

\

When you have finished configuring the filter, click the Submit button.

\ \

Credits

\

\ The Spliced EST track is produced at UCSC from EST sequence data\ submitted to the international public sequence databases by \ scientists worldwide.

\ rna 1 intronGap 30\ est $Organism ESTs psl est $Organism ESTs Including Unspliced 0 57 0 0 0 127 127 127 1 0 0

Description

\

\ This track shows alignments between $organism Expressed\ Sequence Tags (ESTs) in Genbank and the genome.

\ \

Expressed sequence tags are single read (typically\ approximately 500 base) sequences which usually\ represent fragments of transcribed genes. Aligning \ regions (usually exons) are shown as black boxes \ connected by lines for gaps (usually spliced out introns). \ In full display mode, arrows on the introns\ indicate the direction of transcription. In the\ December 2001 assembly and later, this direction is\ taken by looking at the splice sites. In previous\ assemblies, the direction of transcription was taken from \ the Genbank annotations, which frequently were inaccurate.

\ \

Strand information provided for ESTs (+/-) indicates the\ direction of the match between the EST and the matching\ genomic sequence. It bears no relationship to the direction\ of transcription of the RNA with which it might be associated.\ \

Method

\

To make an EST, RNA is isolated from cells and reverse\ transcribed into cDNA. Typically, the cDNA is cloned\ into a plasmid vector, and a read taken from the 5'\ and/or 3' primer. For most - but not all - ESTs, the\ reverse transcription is primed by an oligo-dT, which\ hybridizes with the poly-A tail of mature mRNA. The\ reverse transcriptase may or may not make it to the 5'\ end of the mRNA, which may or may not be degraded.

\ \

In general, the 3' ESTs mark the end of transcription\ reasonably well, but the 5' ESTs may end at any point\ within the transcript. Some of the newer cap-selected\ libraries are starting to hit transcription start\ reasonably well. Before the cap-selection techniques\ emerged, some projects used random rather than poly-A\ priming in an attempt to get sequence distant from the\ 3' end. These projects were successful at this, but as\ a side effect also deposited sequences from unprocessed\ mRNA and perhaps even genomic sequences into the EST databases.\ (Even outside of the random-primed projects, there is a\ degree of non-mRNA contamination.) Because of this, a\ single unspliced EST should be viewed with considerable\ skepticism. However, because the $organism 3' UTRs are quite\ long, the splicing requirement does eliminate many genuine 3'\ ESTs.

\ \

To generate this track, $organism ESTs from Genbank are aligned \ against the genome using the \ blat \ program. Note that the maximum intron length\ allowed by blat is 500,000 bases, which may eliminate some ESTs with very \ long introns that might otherwise align. When a single \ EST aligns in multiple places, the alignment having the \ highest base identity is found. Only alignments that have \ a base identity level within 0.1% of the best are kept. \ Alignments must also have at least 98% base identity to be kept.

\ \

Using the Filter

\

The track filter can be used to change the color or include/exclude a subset of \ individual items within a track. This is helpful when many items are shown in the \ track display, especially when only some are relevant to the current task. To use the\ filter:\

    \
  1. Enter a value in one or more of the text boxes to filter the EST display. For\ example, to apply the filter to all ESTs expressed in the liver, type "liver" in the \ tissue box. For a list of permissible filter values, consult the non-positional table in\ the Table Browser that corresponds to the factor on which you wish to filter. For\ example, the non-positional table "tissue" contains all of the types of tissues\ that can be entered into the tissue text box. Wildcards can also be used in the\ filter.\
  2. If filtering on more than one value, choose the desired combination\ logic. If "and" is selected, only ESTs that match all of the filter criteria will\ be highlighted. If "or" is selected, ESTs that match any 1 of the filter criteria\ will be highlighted.\
  3. Choose the color or display characteristic that should be used to highlight or\ include/exclude the filtered items. If "exclude" is chosen, the browser will not \ display ESTs that match the filter criteria. If "include" is selected, the browser \ will display only those ESTs that match the filter criteria.\

\

When you have finished configuring the filter, click the Submit button.

\ \

Credits

\

\ The $Organism EST track is produced at UCSC from EST sequence data\ submitted to the international public sequence databases by \ scientists worldwide.

\ rna 1 intronGap 30\ xenoMrna Non$Organism mRNAs psl xeno Non$Organism mRNAs from Genbank 1 63 0 0 0 127 127 127 1 0 0

Description

\

\ This track displays translated \ blat\ alignments of\ non-$organism vertebrate and invertebrate mRNA from Genbank.

\ \

The strand information (+/-) for this track is in two parts. The\ first + indicates the orientation of the query sequence whose\ translated protein produced the match (here always 5' to 3', hence +).\ The second + or - indicates the orientation of the matching \ translated genomic sequence (+ or -).\ \ \

Method

\

\ The alignments were passed through a near-best-in-genome filter.

\ \

Using the Filter

\

The track filter can be used to color, include, or exclude a subset of individual \ items within a track. This is helpful when many items are shown in the track\ display, especially when only some are relevant to the current task. To use the\ filter:\

    \
  1. Enter a value in one or more of the text boxes to filter the mRNA display. For\ example, to apply the filter to all brain mRNAs, type "brain" in the \ tissue box. For a list of permissible filter values, consult the non-positional table in\ the Table Browser that corresponds to the factor on which you wish to filter. For\ example, the non-positional table "tissue" contains all of the types of tissues\ that can be entered into the tissue text box. Wildcards can also be used in the\ filter.\
  2. If filtering on more than one value, choose the desired combination\ logic. If "and" is selected, only mRNAs that match all of the filter criteria will\ be highlighted. If "or" is selected, mRNAs that match any 1 of the filter criteria\ will be highlighted.\
  3. Choose the color or display characteristic that will be used to highlight or\ include/exclude the filtered items. If "exclude" is chosen, the browser will not \ display mRNAs that match the filter criteria. If "include" is selected, the browser \ will display only those mRNAs that match the filter criteria.\

\

When you have finished configuring the filter, click the Submit button.

\ rna 1 xenoEst Non$Organism ESTs psl xeno Non$Organism ESTs from Genbank 0 65 0 0 0 127 127 127 1 0 0 http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?form=4&db=n&term=$$

Description

\

\ This track displays translated \ blat\ alignments of\ non-$organism vertebrate ESTs from Genbank.

\ \

The strand information (+/-) for this track is in two parts. The\ first + or - indicates the orientation of the query sequence whose\ translated protein produced the match. The second + or - indicates the\ orientation of the matching translated genomic sequence. Because the two\ orientations of a DNA sequence give different predicted protein sequences,\ there are four combinations. ++ is not the same as --; nor is +- the same\ as -+.\ \

Method

\

\ To generate this track, the ESTs are aligned against the genome using the blat\ program. The alignments are passed through a piecewise near-best-in-genome\ filter.

\ \

Using the Filter

\

The track filter can be used to change the color or include/exclude a subset of \ individual items within a track. This is helpful when many items are shown in the \ track display, especially when only some are relevant to the current task. To use the\ filter:\

    \
  1. Enter a value in one or more of the text boxes to filter the EST display. For\ example, to apply the filter to all ESTs expressed in the liver, type "liver" in the \ tissue box. For a list of permissible filter values, consult the non-positional table in\ the Table Browser that corresponds to the factor on which you wish to filter. For\ example, the non-positional table "tissue" contains all of the types of tissues\ that can be entered into the tissue text box. Wildcards can also be used in the\ filter.\
  2. If filtering on more than one value, choose the desired combination\ logic. If "and" is selected, only ESTs that match all of the filter criteria will\ be highlighted. If "or" is selected, ESTs that match any 1 of the filter criteria\ will be highlighted.\
  3. Choose the color or display characteristic that should be used to highlight or\ include/exclude the filtered items. If "exclude" is chosen, the browser will not \ display ESTs that match the filter criteria. If "include" is selected, the browser \ will display only those ESTs that match the filter criteria.\

\

When you have finished configuring the filter, click the Submit button.

\ \

Credits

\

\ This track is produced at UCSC from EST sequence data submitted to the\ international public sequence databases by scientists worldwide.

\ rna 1 tigrGeneIndex TIGR Gene Index genePred Alignment of TIGR Gene Index TCs Against the $Organism Genome 0 68 100 0 0 177 127 127 0 0 0 http://www.tigr.org/tigr-scripts/tgi/tc_report.pl?$$

Description

\

This track displays alignments of the TIGR Gene Index (TGI)\ against the $organism genome. The TIGR Gene Index is based\ largely on assemblies of EST sequences in the public databases.\ See \ www.tigr.org for more information about TIGR and the Gene Index.

\

Credits

\

Thanks to Foo Cheung for converting these data into a track\ for the browser.

\ rna 1 uniGene_2 UniGene bed 12 UniGene Alignments and SAGE Info 0 69 0 0 0 127 127 127 1 0 0

Description: Serial Analysis of Gene Expression (SAGE)\ is a quantative measurement gene expression. Data is presented for every cluster contained \ in the browser window and the selected cluster name is highlighted in red. All data are from \ the repository at the SageMap \ project downloaded Jul 26, 2002. Selecting the UniGene cluster name will display SageMap's page for that cluster.\

Brief Methodology: SAGE counts are produced \ by sequencing small "tags" of DNA believed to be associated with a \ gene. These tags are produced by attatching poly-A RNA to oligo-dT \ beads. After synthesis of double stranded cDNA transcripts are \ cleaved by an anchoring enzyme (usually NIaIII). Then small tags are \ produced by ligation with a linker containing a type IIS restriction \ enzyme site and cleavage with the tagging enzyme (usually BsmFI). The \ tags are then concatenated together and sequenced. The frequency of each \ tag is counted and used to infer expression level of transcripts that can \ be matched to that tag. All SAGE data presented here were mapped to UniGene \ transcripts by the SageMap \ project at NCBI .



\ \ rna 1 rnaCluster Gene Bounds bed 12 Gene Boundaries as Defined by RNA and Spliced EST Clusters 0 71 200 0 50 227 127 152 0 0 0

Description

\

\ This track shows the boundaries of genes and the direction of\ transcription as deduced from clustering spliced ESTs and mRNAs\ against the genome. When there are many spliced variants\ of the same gene, this track shows the variant that\ spans the greatest distance in the genome.

\ \

Method

\

\ ESTs and mRNAs from Genbank are aligned against the genome\ with the \ blat\ program, and filtered to keep only those alignments\ that have at least 97.5% base identity within the \ aligning blocks. When multiple alignments occur, only the\ alignments with a percentage identity within 0.2% of the\ best alignment are kept. ESTs that align without any\ introns are discarded. Blocks that are less than 130 bases\ and are not next to an intron are discarded. Blocks smaller\ than 10 bases are discarded. The orientations of the \ ESTs and mRNAs are deduced from the GT/AG splice sites\ at the introns, and ESTs and mRNAs with overlapping blocks\ on the same strand are merged into clusters. Only the\ extent and orientation of the clusters are shown here.\

\

Credits

\

\ This track was generated at UCSC by Jim Kent using data\ submitted to Genbank by scientists worldwide.

\ rna 1 dbtssAli DBTSS mRNA psl . RefSeq mRNA Extended to the 5' End from DBTSS 0 75 0 0 100 127 127 177 0 0 0

Description

\

\ Although the information of cDNAs is indispensable for analyzing gene function, most of the cDNA sequences stored in
\ current databases are imperfect in the sense that they lack the precise information of 5' end termini. To overcome this
\ difficulty, a team at the Human Genome Center, Institute of Medical Science, University of Tokyo developed an oligo-capping
\ method to obtain full-length cDNAs, the information of which has been partly deposited in public databases. In this
\ study, they further constructed human cDNA libraries enriched in clones containing the cap structure to systematically
\ explore the 5' end structure of expressed genes. Of about 284,687 5' end sequences obtained, 155,304 corresponded to
\ cDNA sequences of known genes (8,996 genes) and are presented in the DataBase of Transcriptional Start Sites (DBTSS).
\ Sequence comparison between the DBTSS entries and those of the reference sequence database, RefSeq, revealed that
\ 4,802 (34.2 %) of RefSeq sequences should be extended towards the 5' ends. The \ team also mapped each sequence on
\ the human draft genome sequence to identify its transcriptional start site, which provided more detailed information
\ on distribution patterns of transcriptional start sites and adjacent regulatory regions.\

\ \

Credits

\ The data were contributed by the \ \ Database of Transcriptional Start Sites. Mouse sequence data are provided by the
\ Mouse Genome Sequencing Consortium.\ \ rna 1 cpgIsland CpG Islands bed 4 + CpG Islands (Islands < 300 Bases are Light Green) 0 76 0 100 0 128 228 128 0 0 0

Description

\

\ CpG islands are associated with genes, particularly housekeeping\ genes, in vertebrates. CpG islands are typically common near\ transcription start sites, and may be associated with promoter\ regions. Normally a C (cytosine) base followed immediately by a G (guanine) base (a CpG) is rare in\ vertebrate DNA because the C's in such an arrangement tend to be\ methylated. This methylation helps distinguish the newly synthesized\ DNA strand from the parent strand, which aids in the final stages of\ DNA proofreading after duplication. However, over evolutionary time\ methylated C's tend to turn into T's because of spontaneous\ deamination. The result is that CpG's are relatively rare unless\ there is selective pressure to keep them or a region is not methylated\ for some reason, perhaps having to do with the regulation of gene\ expression. CpG islands are regions where CpG's are present at\ significantly higher levels than is typical for the genome as a whole.\

\ \

Method

\

\ CpG islands are predicted by searching the sequence one base at a\ time, scoring each dinucleotide (+17 for CG and -1 for others) and\ identifying maximally scoring segments. Each segment is then\ evaluated to determine GC content (>=50%), length (>200), and ratio of\ observed proportion of CG dinucleotides to the expected proportion on\ the basis of the GC content of the segment (>0.6). \

\ \

Credits

\

\ This track was generated \ using a\ modification of a program developed by G. Miklem and L. Hillier. \

\ \ regulation 1 nci60 NCI60 bed 15 + Microarray Experiments for NCI 60 Cell Lines 0 84 0 0 0 127 127 127 0 0 0 \

Description

\ \

Expression data from "\ Systematic variation in gene expression patterns in human cancer cell\ lines"[pubmed],\ Ross et al. Nat Genet 2000 Mar;24(3):227-35. cDNA microarrays were\ used to explore the variation in expression of approximately 8,000\ unique genes among the 60 cell lines used in the National Cancer\ Institute's screen for anti-cancer drugs. The authors have provided a\ web supplement \ where more data and experimental description can be obtained. cDNA\ probes were placed on the draft human genome using genebank sequences\ referenced by the IMAGE clone ids. \ \

The data are shown in a tabular format in which each column of\ colored boxes represents the variation in transcript levels for a\ given cDNA across all of the array experiments, and each row\ represents the measured transcript levels for all genes in a single\ sample. The variation in transcript levels for each gene is\ represented by a color scale, in which red indicates an increase in\ transcript levels, and green indicates a decrease in transcript\ levels, relative to the reference sample. The saturation of the color\ corresponds to the magnitude of transcript variation. A black color\ indicates an undetectable change in expression, while a gray box\ indicates missing data.\ \

Display Options

\ This track has filter options to customize tissue types presented and\ the color of the display.\ \

Cell Line: This option is only valid when the track is \ displayed in full. It determines how the experiments are displayed. The\ options are:\

\ Color Scheme: \ Data are presented using two color false display. By default\ the Brown/Botstein colors of red -> positive log ratio, green -> negative log ratio are used.\ However, blue can be substituted for green for those who are color blind.\ \

Details Page

\ On the details page, the probes presented\ correspond to those contained in the window range displayed on the Genome\ Browser. The exon probe and experiment selected are highlighted in\ blue.\ regulation 1 affyRatio GNF Ratio bed 15 + GNF Gene Expression Atlas Ratios Using Affymetrix GeneChips 0 86 0 0 0 127 127 127 0 0 0

Description

\

This track shows expression data from GNF (The Genomics Institute of the Novartis Research Foundation)\ using Affymetrix GeneChips.\ Chipset information is available using the Filter control.

\ \

Methods

\

For detailed information about the experiments, see Su et al., \ "Large-scale analysis of the human and mouse transcriptomes.", \ PNAS, Mar 19, 2002. Alignments displayed on the track\ correspond to the target sequences used by Affymetrix from which to\ choose probes.

\

In dense mode, the track color denotes the average signal over all\ experiments on a log base 2 scale. Lighter colors correspond to lower signals \ and darker colors correspond to higher signals. In full\ mode, the color of each item represents the log base 2 ratio of the signal of\ that particular experiment to the median signal of all experiments for that probe.\

More information about individual probes and probe sets is available at\ Affymetrix's netaffx.com website. \ \

Using the Filter

\

The track filter, accessible via the gray bar at the left in the\ graphical display, can be used to change the display mode, group the displayed\ results, and change the display colors. \

\ \

Credits

\

Thanks to GNF for providing these data.

\ regulation 0 chip U95\ expScale 3.0\ expStep 0.5\ expTable affyExps\ affyTranscriptome Transcriptome sample Affymetrix Experimentally Derived Transcriptome 0 89 100 50 0 0 0 255 0 0 2 chr22,chr21,

Description

\

\ Transcriptome data for chromosomes 21 and 22 from Affymetrix, as described in \ "Large-Scale Transcriptional Activity in Chromosomes 21 and 22",\ Kapranov, P., Cawley, S. E., Drenkow, J., Bekiranov, S, Strausberg,\ R. L., Fodor, S.P.A. and Gingeras, T.R.. In general, the data presented\ is the perfect match - mis-match value. Different experiments were\ normalized by setting the average value to be the same for each\ chip. Replicates for different cell types were averaged together to\ produce the data seen in "full" mode for each cell type. In dense\ mode, or at the top of the track in full mode, "Transcriptome" displays\ the maximum value over all experiments for that probe, the idea being\ to paint as many transcribed regions as possible. \

\ To present a more\ interpretable display when zoomed out, averages have been precalculated\ over the chromosome at two different resolutions in addition to the\ raw data. For example, when zoomed out, there may appear to be a peak at\ the center of a gene rather than a signal at every exon. Zooming in\ will reveal the "raw" data for that region.\

\ NOTE: Affymetrix transcriptome annotations appear only on chromosomes 21 and 22.\ \

Credits

\

\ Thanks to Affymetrix for providing these data. Questions/Comments? Email sugnet@cse.ucsc.edu.\ regulation 0 blatFish Tetraodon Blat psl xeno Tetraodon nigroviridis Translated Blat Alignments 1 112 0 60 120 200 220 255 1 0 0

Description

\

This track displays translated alignments of 728 million bases of Tetraodon nigroviridis \ whole genome shotgun reads vs. the draft $organism genome. Areas painted by\ this track are quite likely to be coding regions.

\

Methods

\

The alignments were done \ with blat in translated protein mode requiring 2 nearby 4-mer matches\ to trigger a detailed alignment. The human\ genome was masked with RepeatMasker and Tandem Repeat Finder before \ running blat.

\

Credits

\

Many thanks to Genoscope for \ providing the Tetraodon sequence.

\ compGeno 1 humMusL Mouse Cons sample 0 8 Human/Mouse Evolutionary Conservation Score (std units) 0 118 175 150 128 175 150 128 0 0 0

Description

\

\ This track displays the conservation between the human and mouse genomes for \ 50 bp windows in the human genome that have at least 15 bp aligned to\ mouse. The score for a window reflects the probability that the\ level of observed conservation in that 50 bp region would occur by\ chance under neutral evolution. It is given on a logarithmic scale,\ and thus it is called the "L-score". An L-score of 1 means there is a\ 1/10 probability that the observed conservation level would occur by\ chance, an L-score of 2 means a 1/100 probability, an L-score of 3\ means a 1/1000 probability, etc. The L-scores display as\ "mountain ranges". Clicking on a mountain range, a detail page is\ displayed from which you can access the base level alignments, both\ for the whole region and for the individual 50 bp windows.\

\ \

Methods

\

\ Genome-wide alignments between human and mouse were produced by\ blastz. A set of 50 bp windows in the human genome were determined\ by scanning the sequence, sliding 5 bases at a time, and only those\ windows with at least 15 aligned bases were kept. For each window,\ a conservation score defined by\

\

\ S = sqrt(n/m(1-m))(p-m)\
\
\ was calculated, where n is the number of aligning bases in the\ window, p is the percent identity between human and mouse for these\ aligning bases, and m is the average percent identity for aligned\ neutrally evolving bases in a larger region surrounding the 50 bp\ window being scored. Neutral bases were taken from ancestral repeat\ sequences, which are relics of transposons that were inserted before\ the human-mouse split. To transform S into an L-score, the empirical\ cumulative distribution function CDF(S) = P(x < S)\ is computed from the scores of all windows genome-wide, and\ the L-score is defined as\

\
\ L = -log_10(1 - CDF(S)).\
\
\
\ The L-score\ provides a frequentist confidence assessment. A Bayesian\ calculation of the probability that a window is under\ selection can also be made using a mixture decomposition of\ the empirical density of the scores for all windows\ genome-wide into a neutral and a selected component. Details\ are given in a manuscript in preparation. The results are\ summarized in the table below.\

\
\
\
L-score       Frequentist probability       Bayesian probability\
              of this L-score or greater    that window with this\
              given neutral evolution       L-score is under\
                                            selection\
\
------------------------------------------------------------------\
\
   1                0.1                          0.32 \
  2                0.01                         0.75\
  3                0.001                        0.94\
  4                0.0001                       0.97\
  5                0.00001                      0.98\
  6                0.000001                     0.99\
    7                0.0000001                    >0.99 \
   8                0.00000001                   >0.99\
\
\
\

\ \

Using the Filter

\

The track filter can be used to configure some of the display characteristics\ of the track. \

\ When you have finished configuring the filter, click the Submit button.\ \

Credits

\

\ Thanks to Webb Miller and Scott Schwartz for creating the blastz\ alignments, Jim Kent for post-processing them, and \ Mark Diekhans for scoring the windows and selecting out the ancestral repeats. \ Krishna Roskin created S-scores for these windows. Ryan Weber computed the CDF \ for these S-scores, and created the remaining track display functions. Mouse sequence data are provided by the Mouse Genome Sequencing Consortium.\

\ \ compGeno 0 slamNonCodingMouse Slam Non Coding Mouse bed 5 Slam Predictions of Human/Mouse Conserved Non-Coding Regions 0 120 30 130 210 200 220 255 1 0 0

Description and Credits

\ \

\ Slam predicts coding exons and conserved noncoding regions in a pair of\ homologous DNA sequences, incorporating both statistical sequence properties\ and degree of conservation into predictions. This particular annotation uses the Feb. 2002 (mm2) assembly of the mouse genome. The model is symmetric and the same gene structure (with possibly different exon lengths) is predicted in both sequences. \ \

\ The CNS (conserved non-coding sequence) predictions are ab-initio\ predictions of conserved regions that do not fit in with a gene structure.\ Thus, slam is not simply trying to predict conserved regions to be coding,\ but is classifying such regions according to an overall probabilistic model\ of gene structure. The set of slam CNS predictions is therefore highly\ enriched for conserved non-coding regions.\ \

\ More information and a web server can be found at http://baboon.math.berkeley.edu/~syntenic/slam.html.\ \

\

References

\ M. Alexandersson, S. Cawley, L. Pachter (2003). SLAM - Cross-species Gene Finding and Alignment with a Generalized Pair Hidden Markov Model. Genome Research 13(3):496-502.\

L. Pachter, M. Alexandersson, S. Cawley (2001). \ Applications of Generalized Pair Hidden Markov Models to Alignment and Gene Finding Problems, \ Proceedings of the Fifth Annual International Conference on Computational Molecular Biology (RECOMB 2001).\

L. Pachter , M. Alexandersson, S. Cawley (2002). \ Applications of Generalized Pair Hidden Markov Models to Alignment and Gene Finding Problems, \ Journal of Computational Biology 9(2):389-400.\ \ compGeno 1 blastzTightMouse Tight Mouse psl xeno mm2 Blastz Mouse (Feb. 02), Tight Subset of Best Alignments 0 123 100 50 0 255 240 200 1 0 0

Description

\

\ This track displays blastz alignments of the Feb. 2002 mouse\ draft assembly to the human genome, filtered by axtBest and \ subsetAxt with very stringent constraints as described below. \ \

Each item in the display is identified by the chromosome, strand, and \ location of the match (in thousands). \ \

Methods

\ Blastz uses 12 of 19 seeds and this matrix: \
\ \ \ \ \ \ \
  A C G T
A  91-114 -31-123
C-114 100-125 -31
G -31-125 100-114
T-123 -31-114 91
\
\ O = 400, E = 30, K = 3000, L = 3000, M = 50\

\ A second pass is done at reduced stringency (7mer seeds and\ MSP threshold of K=2200) to attempt to fill in gaps of up to about 10K bp.\ Lineage specific repeats are abridged during this alignment.\

\ AxtBest selects only the best alignment for any given region\ of the genome. \

\ SubsetAxt was run on axtBest-filtered alignments \ with this matrix:\
\ \ \ \ \ \ \
  A C G T
A100-200-100-200
C-200100-200-100
G-100-200100-200
T-200-100-200100
\
\ \ with a gap open penalty of 2000 and a gap extension penalty of 50. \ The minimum score threshold was 3400.\ \

Using the Filter

\

The track filter can be used to turn on the chromosome color track or to \ filter the display output by chromosome.\

\ When you have finished configuring the filter, click the Submit button.\ \

Credits

\ The alignments are contributed by Scott Schwartz from the\ \ Penn State Bioinformatics Group. \ The best in genome filtering is done by UCSC's axtBest and subsetAxt\ programs.\ Mouse sequence data are provided by the \ Mouse Genome Sequencing Consortium. \ \ compGeno 1 otherDb mm2\ blastzBestMouse Best Mouse psl xeno mm2 Blastz Mouse (Feb. 02) Best in Genome Alignments 1 126 100 50 0 255 240 200 1 0 0

Description

\

This track displays blastz alignments of the Feb. 2002 mouse draft\ assembly to the human genome filtered to display only the best alignment for any\ given region of the human genome. The track has an optional\ feature that color codes alignments to indicate the chromosomes from which \ they are derived in the aligning assembly. To activate the color feature,\ click the on radio button next to "Color track based on chromosome".\
\

Methods

\ For blastz, we use 12 of 19 seeds and then score using: \
\ \ \ \ \ \ \
  A C G T
A  91-114 -31-123
C-114 100-125 -31
G -31-125 100-114
T-123 -31-114 91
\
\ O = 400, E = 30, K = 3000, L = 3000, M = 50\

\ We then do a second pass at reduced stringency (7mer seeds and\ MSP threshold of K=2200) to attempt to fill in gaps of up to about 10K bp.\ Lineage specific repeats are abridged during this alignment.\
\ \

Using the Filter

\

The track filter can be used to turn on the chromosome color track or to \ filter the display output by chromosome.\