TSS assembly pipeline for Hs_EPDnew_004
Introduction
This document provides a technical description of the transcription
start site assembly pipeline that was used to generate EPDnew
version 004 for
H. sapiens.
Source Data
Promoter collection:
Name |
Genome Assembly |
Promoters |
Genes |
PMID |
Access data |
UCSC Known Genes
|
Feb 2009 GRCh37/hg19
|
28210
|
18636
|
26590259
|
SOURCE
|
DOC
|
DATA
|
Experimental data:
Assembly pipeline overview
Description of procedures and intermediate data files
1. UCSC Download
Data was downloaded from UCSC Table Browser (11-03-2014) selecting
the following attributes:
- hg19.knownGene
- hg19.ensemblSource
- hg19.kgXref
- hg19.knownToEnsembl
- hg19.refSeqStatus
- hg19.spMrna
Then, transcrips were filtered according to the following rules:
- Transcripts of protein coding genes only (Ensembl
annotation)
- Transcripts must have a RefSeq protein ID
- Transcripts must have a non "n/a" RefSeq status
Gene names were taken from the field "Associated Gene Name". Since
the EPD format doesn\'t allow gene names longer than 18 characters,
we checked whether the names repsected this limitation.
Transcripts with the same TSS position were merged under a common
ID. As a consequence of this the total number of TSS in the list
was 28210.
2. UCSC TSS collection
The UCSC TSS collection is stored as a tab-deliminated text file
conforming to the SGA format under the name:
The six fields in the file contain the following kinds of
information:
- NCBI/RefSeq chromosome id
- "TSS"
- position
- strand ("+" or "-")
- "1"
- TranscriptID..GeneName.
Note that the second and forth fields are invariant.
3. Data import from ENCODE and FANTOM5 CAGE
CAGE Tag Data were downloaded from UCSC ftp-site and FANTOM5
http-site (see links above). The source files are in bam
format. The complete list of files can be found
here for ENCODE and
here for FANTOM5. Bam files were converted into bed files with bamToBed
program. Files were kept and analysed individually.
4. CAGE tags
The compressed versions of these files are available from the MGA
archive (see links above).
5. mRNA 5' tags peak calling
Peak calling for each individual CAGE data file has been carried
out using
ChIP-Peak
on-line tool with the following parameters:
- Window width = 200
- Vicinity range = 200
- Peak refine = N
- Count cutoff = 9999999
- Threshold = 3
6. TSS validation and shifting
Each sample in the collection (mRNA peaks and UCSC TSS) was then
processed in a pipeline aiming at validating transcription start
sites with mRNA peaks. An UCSC TSS was experimentally confirmed if
a CAGE peak lied in a window of 500 bp around it and if it had a
maximum high of at least 3 tags. The validated TSS was then
shifted to the nearest base with the higher tag density.
7. UCSC not-validated TSS
The total number (summing up all samples) of non experimentally
validated TSS was around 3000.
8. Promoter collection for each sample
Each sample in the dataset was used to generate a separate
promoter collection. Potentially, the same transcript could be
validated by multiple samples and it could have different start
sites in different samples. To avoid redundancy, the individual
collections were used as input for an additional step in the
analysis (Assembly pipeline part B).
9. Merging collections and second TSS selection
The 1K promoter collections were merged into a unique file and
further analysed. The promoter of a transcript was mantained in
the list only if validated by at least two samples. Transcript
validated by multiple samples could potentially have the TSS set
on a broader region and not to single position. To avoid such
inconsistency, for each transcript we selected the position that
was validated by the larger number of samples as the true TSS.
10. Filtering
Transcription Start Sites that mapped closed to other TSS that
belonged to the same gene (500 bp window) were merged into a
unique promoter following the same rule: the promoter that was
validated by the higher number of samples was kept.
10. Final EPDnew collection
The 25503 experimentally validated promoter were stored in the
EPDnew database that can be downloaded from our ftp
site. Scientist are wellcome to use our other tools
ChIP-Seq (for
correlation analysis) and
SSA (for motifs analysis
around promoters) to analyse EPDnew database.