The chromosome band track represents the approximate \ location of bands seen on Giemsa-stained chromosomes at\ an 800 band resolution.
\ \Barbara Trask, Vivian Cheung, Norma Nowak and the rest of the BAC Resource\ Consortium used fluorescent in-situ\ hybridization (FISH) to determine a cytogenetic location for \ large genomic clones on the chromosomes.\ For more information about the BAC Resource Consortium, please see\ "Integration of cytogenetic landmarks into the draft sequence of the human genome",\ Nature, \ vol 409, Feb. 2001, pp.953-958 and the accompanying web site\ Human BAC Resource.\ \
Wonhee Jang and Arek Kasprzyk helped determined the location\ of these clones on the October assembled draft human genome\ using the clone sequence where possible and in other cases by\ STS marker and BAC end sequence locations. \ Clone placements are now being determined at UCSC using the same information.
\ \Terry Furey and\ David Haussler developed a program which uses a hidden Markov model\ (HMM) to integrate the range of bands associated with various\ FISHed clones into the most probable arrangement of bands on the\ sequence given the assumptions of the model.
\ \
We would like to thank all of the labs that have contributed to this resource:\
This track shows the location of FISH mapped clones along the \ draft assembly sequence. The locations of these clones were\ contributed as a part of The BAC Resource Consortium \ ("Integration of cytogenetic landmarks into the draft sequence of the human genome",\ Nature, \ vol 409, Feb. 2001, pp.953-958).
\ \More information about the BAC clones including how it can be obtained can be found at the \ Human BAC Resource\ and the Clone Registry\ web sites hosted by NCBI.\ You can view the entry for this clone in the Clone Registry by clicking on the clone name\ at the top of the page.
\ \ \We would like to thank all of the labs that have contributed to this resource:\
This track shows locations of STSs (Sequence Tagged Sites)\ along the draft assembly. These STSs have been mapped using \ either genetic (Genethon and Marshfield maps),\ radiation hybridization (the Stanford, Whitehead RH, and GeneMap99 maps) or\ YAC mapping (the Whitehead YAC map) techniques. \ Prior to August 2001, this track also\ shows the approximate position of FISH mapped clones.\ Starting in August 2001, the FISH clones have separated into a new\ track of their own.
\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:
\This track shows locations of STSs (Sequence Tagged Sites)\ along the draft assembly. These STSs have been mapped using \ either genetic (Genethon and Marshfield maps),\ radiation hybridization (the Stanford, Whitehead RH, and GeneMap99 maps) or\ YAC mapping (the Whitehead YAC map) techniques. \ Prior to August 2001, this track also\ shows the approximate position of FISH mapped clones.\ Starting in August 2001, the FISH clones have separated into a new\ track of their own.
\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:
\Isochores describe a region of a chromosome where the CG-content is\ either higher or lower than the whole genome average (42%). A CG-rich\ isochore is given a dark color, while a CG-poor isochore is a light\ color.
\Isochores were determined by first calculating the CG-content of 100,000bp\ windows across the genome. These windows were either labeled H or L\ depending on whether the window contained a higher or lower GC-content\ than average. A two-state HMM was created in which one state represented\ GC-rich regions, and the other GC-poor. It was trained using the first 12\ chromosomes. The trained HMM was used to generate traces over all chromosomes.\ These traces define the boundaries of the isochores,\ and their type (GC-rich or AT-rich).
\ gcPercent GC Percent bed 4 + Percentage GC in 20,000 Base Windows 0 6.00 0 0 0 127 127 127 1 0 0 The GC percent track shows the percentage of bases that are G or C in\ a 20,000 base window. The average GC percent across the human genome\ is 41%. Windows with high GC content are drawn more darkly than windows\ with low GC content. High GC content is associated with gene rich areas.\ ctgPos Map Contigs Physical Map Contigs 0 7.00 150 0 0 202 127 127 0 0 0 The map contigs track shows the locations of contigs of clones\ on the physical map. In assembly versions before the August 6\ 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'\ in Nature volume 409 pages 934-941. Starting with the August\ 6 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\ UCSC assemblies. The clone contigs in this merged map are shown in\ this track.\ gold Assembly bed 3 + Assembly from Fragments 0 8.00 150 100 30 230 170 40 0 0 0This track shows the UCSC assembly of the human genome.\ This assembly merges contigs from overlapping draft 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 in alternating gold and\ brown the path through the draft and finished clones (aka the\ golden path) used to create the assembled sequence. Where there\ are gaps in the path there are spaces 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.
\ \ gap Gap bed 3 + Gap Locations 1 9.00 0 0 0 127 127 127 0 0 0 This track depicts gaps in the assembly. These gaps will, with the\ exception of intractable heterochromatic gaps, 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 principle \ types of gaps:\BAC end sequences are placed on the assembled sequence using\ Jim Kent's BLAT program.
\ \A valid pair of BAC end sequences must be\ at least 50Kb but no more than 600Kb away from each other, and \ the orientation of the first BAC end sequence must be "+" and\ the orientation of the second BAC end sequnece must be "-".
\ \ Additional information about the clone including how it\
can be obtained may be found at the \
NCBI Clone Registry.\
You can view the entry for this clone in the registry by clicking on the clone name\
at the top of the page.\
genomicDups Duplications bed 6 + Duplications of >1000 Bases Sequence 0 10.50 170 0 0 160 150 0 0 0 0 This region was detected as a genomic duplication within the golden path. \
Duplications of 99% or greater similarity, which are likely missed overlaps, \
are shown as red. Duplications of 98% - 99% similarity are shown as yellow. \
Duplications of 90% - 98% similarity are shown as shades of gray. 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. For a \
description of the 'fuguization' detection method see \
Bailey, et al (2001) Genome Res 11:1005-17. \
The data was provided by Jeff Bailey and Evan Eichler.\
\
dupes Duplications bed 6 . Duplications of >98% Identity >1kb 1 11.00 0 0 0 127 127 127 0 0 0
cgh UCSF CGH bed 4 + UCSF Comparative Genomic Hybridizations 0 11.50 0 0 0 127 127 127 0 1 0
mcnBreakpoints MCN Breakpoints bed 4 + MCN breakpoints 0 11.70 0 0 0 127 127 127 0 1 0
refGene Known Genes genePred refPep refMrna Known Genes (from RefSeq) 2 12.00 20 20 170 137 137 212 0 0 0
This track contains the Sanger Centre annotations of\ chromosome 22. The raw data for this track was provided\ by Ian Dunham on a slightly different revision of the\ chromosome 22 sequence. Victoria Haghighi remapped this\ to the version of the chromosome 22 sequence used here,\ and converted the data to a standard GTF format.
\ sanger20 Sanger 20 genePred Sanger Institute Chromosome 20 Genes 2 13.00 0 100 180 127 177 217 0 0 1 chr20,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 being 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.
\Currently over 10% of the human genome including two complete\ chromosomes, 20 \ (\ http://www.sanger.ac.uk/HGP/Chr20/) \ and 22 \ (\ http://www.sanger.ac.uk/HGP/Chr22/) \ have been annotated by The Sequence\ Annotation Team in collaboration with the individual Chromosome Project\ Teams \ (\ http://www.sanger.ac.uk/HGP/Humana/). \ Email enquires can be sent to \ humquery@sanger.ac.uk.\ freen Pet Freen psl . Jims Pet Freen 0 13.01 100 0 100 177 127 177 0 0 1 chr22, sanger22pseudo Sanger 22 Pseudo genePred Sanger Center Chromosome 22 Pseudogenes 0 13.10 30 130 210 142 192 232 0 0 1 chr22, genieAlt Affy Genes genePred geniePep Affymetrix Gene Predictions 1 14.00 125 0 150 190 127 202 0 0 0
Genie predictions are based on \ Affymetrix's \ Genie gene finding software. Genie is a generalized HMM \ which accepts constraints based on mRNA and EST data.
\ acembly Acembly Genes genePred acemblyPep acemblyMrna Acembly Gene Predictions With Alt-splicing 1 14.50 155 0 125 205 127 190 0 0 0 http://www.ncbi.nlm.nih.gov/AceView/av.cgi?db=GPE&l=$$\ This track shows gene models reconstructed solely from\ mRNA and EST evidence by Danielle-et-Jean Thierry-Mieg\ and Vahan Simonyan using the Acembly program.\
\ \ aceTest Acembly Test genePred Acembly Test Predictions 2 14.51 195 50 165 225 152 210 0 1 0 http://www.ncbi.nlm.nih.gov/AceView/av.cgi?db=GP&l=$$ ensGene Ensembl Genes genePred ensPep Ensembl Gene Predictions 1 15.00 150 0 0 202 127 127 0 0 0 http://www.ensembl.org/perl/transview?transcript=$$ These gene predictions are from Project Ensembl.\ softberryGene Fgenesh++ Genes genePred softberryPep Fgenesh++ Gene Predictions 1 16.00 0 100 0 127 177 127 0 0 0Fgenesh++ predictions are based on Softberry's gene finding software. \ Fgenesh++ uses both HMMs and protein similarity to find genes in a \ completely automated manner. See the \ paper "Ab initio gene finding in Drosophila genomic DNA", \ Genome Research 10(5) 516-522 for more information.
\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.\ \ softPromoter TSSW Promoters bed 5 + TSSW Promoter Predictions 1 17.00 0 100 0 127 177 127 0 0 0 genscan Genscan Genes genePred genscanPep Genscan Gene Predictions 1 17.50 170 100 0 212 177 127 0 0 0
This track shows predictions from Chris Burge's program GENSCAN.\ \ genscanExtra Genscan Extra bed 6 Genscan Extra (Suboptimal) Exon Predictions 0 17.60 180 90 0 217 172 127 0 0 1 chr22, mrna Human mRNAs psl . Human mRNAs from Genbank 2 18.00 0 0 0 127 127 127 1 0 0
The Spliced EST track shows Expressed Sequence Tags \ (ESTs) from Genbank that show signs of splicing when\ aligned against the genome. Requiring splicing reduces\ the level of contamination in the EST databases drastically\ at the expense of eliminating many geniune 3' ESTs.\ Please see also the Human EST track.
\Expressed sequence tags are single read (typically\ approximately 500 base) sequences which usually\ represent fragments of transcribed genes. Aligning \ regions (exons usually) are shown as black boxes \ connected by lines for gap (spliced out introns \ usually). In full display, arrows on the introns\ indicate the direction of transcription. ESTs taken\ from the 3' end of the transcript are drawn in deep\ red in full mode. 5' ESTs are drawn in deep blue.\ Beware that the direction arrows on the "introns" are \ unreliable due to uncertainties in the Genbank annotations, though \ the sense strand can often be inferred from the GT-AG splice \ donor/acceptor rule\ \
To make an EST, RNA is isolated from cells and reverse\ transcribed into cDNA. The cDNA is typically 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 however. 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 since the human 3' UTRs are quite\ long requiring splicing does eliminate many genuine 3'\ ESTs.
\ \To generate this track human ESTs from Genbank are aligned \ against the genome using the BLAT program. When a single \ EST aligns in multiple places the alignment having the \ highest base identity is found. Only alignment that have \ a base identity level within 1% of the best are kept. \ Alignments must also have at least 93% base identity to be kept.
\ \To make an EST, RNA is isolated from cells and reverse\ transcribed into cDNA. The cDNA is typically 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 however. 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 since the human 3' UTRs are quite\ long requiring splicing does eliminate many genuine 3'\ ESTs.
\ \To generate this track human ESTs from Genbank are aligned \ against the genome using the BLAT program. When a single \ EST aligns in multiple places the alignment having the \ highest base identity is found. Only alignment that have \ a base identity level within 1% of the best are kept. \ Alignments must also have at least 93% base identity to be kept.
\ \This track displays alignments of the TIGR Gene Index (TGI)\ against the human genome. The TIGR Gene Index is based\ largely on assemblies of EST sequences in the public databases.\ Please click the outside link above for detailed information from\ the TIGR web site on this item. See \ \ www.tigr.org for more information about TIGR and the Gene Index.
\ \Thanks to Foo Cheung for converting this data into a track\ for the browser.
\ uniGene UniGene psl . UniGene Alignments and SAGE Info 1 20.50 0 0 0 127 127 127 0 0 0 mgc_mrna MGC mRNAs psl . Mammalian Gene Collection mRNAs 0 21.00 0 0 0 127 127 127 1 1 0 cpgIsland CpG Islands bed 4 + CpG Islands. (Islands < 400 Bases are Light Green) 0 22.00 0 100 0 128 228 128 0 0 0CpG islands are associated with genes, particularly housekeeping genes, in vertebrates. \ CpG islands are particularly common near transcription start sites, and may be associated \ with promoter regions. Normally a C followed immediately by a G (a CpG) \ is rare in vertebrate DNA since 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 spontanious 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. \ The CpG islands displayed in this browser are all also at least 200 \ bases long, and have a GC content of at least 50%.
\ \ xenoMrna Nonhuman mRNA psl xeno Nonhuman mRNAs from Genbank 1 23.00 0 0 0 127 127 127 1 0 0 This track displays translated blat alignments of\ non-human vertebrate mRNA from Genbank. The alignments\ were passed through a piecewise near-best-in-genome\ filter.\ xenoBestMrna Other Best mRNAs psl xeno Nonhuman mRNAs from Genbank Best in Genome Alignments 0 23.10 0 0 0 127 127 127 1 1 0 This track displays translated blat alignments of\ non-human vertebrate mRNA from Genbank. The alignments\ were passed through a near-best-in-genome filter.\ xenoEst Nonhuman EST psl xeno Nonhuman ESTs from Genbank 0 23.20 0 0 0 127 127 127 1 0 0 http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?form=4&db=n&term=$$ This track displays translated blat alignments of\ non-human vertebrate ESTs from Genbank. The alignments\ were passed through a piecewise near-best-in-genome\ filter.\ blatMouse Mouse Blat psl xeno Mouse Translated Blat Alignments 1 24.00 100 50 0 255 240 200 1 0 0This track displays alignments of 16 million mouse whole genome shotgun \ reads (3x coverage) vs. the draft human genome. The alignments were done \ with BLAT in translated protein mode requiring two perfect 4-mer hits \ within 100 amino acids of each other to trigger an alignment. The human \ genome was masked with RepeatMasker and Tandem Repeat Finder before \ running BLAT. Places where more than 150 reads aligned were filtered out \ as were alignments of greater than 95% base identity (to avoid human \ contaminants in the mouse data).
\This track displays the best single alignment of each of the\ mouse whole genome shotgun reads. It was computed in the same\ manner as the Blat Mouse track, but when a read aligned multiple\ places all the alignments are displayed in that track, while\ only the best alignment is displayed in this track. On occassion\ the alignment score may be equivalent in multiple places in which\ case all equivalent 'best' alignments are displayed.
\The Exonerate mouse shows regions of homology with the\ mouse based on Exonerate alignments of mouse random reads\ with the human genome. The data for this track was kindly provided by\ Guy Slater, Michele Clamp, and Ewan Birney at\ Ensembl.
\ phMouseAli PH Mouse Align bed 5 + Pattern Hunter Human/Mouse Alignments 0 25.30 100 50 0 255 240 200 1 0 1 chr22,This track displays the mouse reference alignment produced by\ Pattern Hunter.\ phMouse PH Mouse Ecores bed 6 Pattern Hunter Mouse/Human Evolutionarily Conserved Regions 1 25.50 100 50 0 255 240 200 1 0 0
PATTERNHUNTER is a highly sensitive and efficient program for\ finding homologies within one, or between two DNA sequences.\ On very long sequences it runs faster than MegaBlast while\ being more sensitive than Blastn (at its default settings).
\This track was produced by having PATTERNHUNTER index each human chromosome \ 22 and processing all mouse reads in turn, looking\ for double hits of weight 11 (using size 18 words with 7 don't cares in the\ pattern 111010011001010111) to extend from and form gapped alignments.
\More information about PATTERNHUNTER is available at \ Bioinformatics\ Solutions Inc. See also PatternHunter: Faster and More Sensitive Homology Search; M. Li, B. Ma, and J. Tromp; Bioinformatics in press.
\ \ fiberMouse Fiberglass Mouse bed 4 . Mouse/Human Evolutionarily Conserved Regions (Fiberglass) 0 25.60 100 50 0 177 152 127 0 0 0 blastzMouse Blastz Mouse bed 5 + Merged Blastz Mouse Alignments 1 25.80 100 50 0 255 240 200 1 0 0 mouseRefHCons HighCon MouseRef bed 5 + Highly Conserved Reference Mouse Alignments 1 25.81 100 50 0 255 240 200 1 0 1 chr22, mouseRefMDup ModDup MouseRef bed 5 + Moderately Duplicated Reference Mouse Alignments 1 25.82 100 50 0 255 240 200 1 0 1 chr22, avidRepeat Avid Rep Mouse bed 5 . Repeating Regions Conserved in Avid Mouse/Human Alignments 0 25.90 100 50 0 255 240 200 1 0 0 This track shows regions of the human genome which align to\ a large number of regions in the mouse genome. The alignments\ were computed with the Avid program. Thanks to Ivan Ovcharenko,\ Inna Dubchak and Lior Pachter for contributing this track.\ avidUnique Avid Mouse bed 5 . Regions Conserved in Avid Mouse/Human Alignments 1 25.90 100 50 0 255 240 200 1 0 0 http://pipeline.lbl.gov/cgi-bin/zBrowser.pl?chrom=$s&from=$[&to=$]&hg=$D&dGenome=dGenome2 This track shows regions of the human genome which align to\ the mouse genome, excluding repetitive elements. The alignments \ were computed with the Avid program. Thanks to Ivan Ovcharenko, \ Inna Dubchak and Lior Pachter for contributing this track.\ exoFish Exofish Ecores bed 5 . Exofish Tetraodon/Human Evolutionarily Conserved Regions 1 27.00 0 60 120 200 220 255 1 0 0 http://www.genoscope.cns.fr/proxy/cgi-bin/exofish.cgi?Id=$$&Mode=IdThe Exofish track shows regions of homology with the \ pufferfish Tetraodon nigroviridis. This information \ was provided by Olivier Jaillon and Hugues Roest Crollius at Genoscope. \ For further information and other Exofish tools please visit the \ \ Genoscope Exofish web site, or \ email \ exofish@genoscope.cns.fr. The following paper also describes \ exofish: 'Estimate of human gene number provided by \ genome-wide analysis using Tetraodon nigroviridis \ DNA sequence' Nature Genetics volume 25 page 235, \ June 2000.
\ blatFish Fish Blat psl xeno Tetraodon nigroviridis Translated Blat Alignments 0 28.00 0 60 120 200 220 255 1 1 0 tet_waba Tetraodon Tetraodon nigroviridis Homologies 1 29.00 50 100 200 85 170 225 0 0 0 rnaGene RNA Genes bed 6 + Non-coding RNA Genes (dark) and Pseudogenes (light) 0 30.00 170 80 0 230 180 130 0 0 0This track shows where non-protein coding RNA genes and\ pseudo-genes are located. This data was kindly provided by\ Sean Eddy at Washington University.
\ snpNih Overlap SNPs bed 4 . Single Nucleotide Polymorphisms (SNPs) from Clone Overlaps 1 31.00 0 0 0 127 127 127 0 0 0 This track shows locations of Single Nucleotide Polymorphisms\ detected primarily by looking at overlaps between clones that\ cover the same region of the genome. Thanks to the SNP Consortium \ and NIH for providing this data.\ snpTsc Random SNPs bed 4 . Single Nucleotide Polymorphisms (SNPs) from Random Reads 1 32.00 0 0 0 127 127 127 0 0 0 This track shows locations of Single Nucleotide Polymorphisms\ detected by aligning reads from random genomic clones from\ a diverse pool of human DNA against the genome. Thanks to \ the SNP Consortium and NIH for providing this data.\ \ perlegen Haplotype Blocks bed 12 Perlegen Common High-Resolution Haplotype Blocks. 1 33.00 0 0 0 127 127 127 1 0 1 chr21, http://www.perlegen.com/haplotype/blk/$$.htmlThe Simple Tandem Repeats were located with the program \ Tandem Repeat Finder \ by G. Benson
\ rosettaTe Rosetta T. E. bed 4 + Rosetta Confirmed Exon Data 1 36.00 0 0 0 127 127 127 0 1 1 chr22, rosettaPe Rosetta P. E. bed 4 + Rosetta Predicted Exon Data 1 37.00 0 0 0 127 127 127 0 1 1 chr22, nci60 NCI60 bed 15 + Microarray Experiments for NCI 60 Cell Lines 0 38.00 0 0 0 127 127 127 0 1 0 cghNci60 CGH NCI60 bed 15 + Comparative Genomic Hybridization Experiments for NCI 60 Cell Lines 0 39.00 0 0 0 127 127 127 0 1 0