Few Questions about PeakSeq and STAT1 Data

I was hoping to use your STAT1 peak results to test a binding site
prediction program that I am developing as part of my PhD project.
I have looked at the files on your source website. For the moment, I am hoping for STAT1 and Control files, which indicate peak location, height, and width, and what processing has been done to achieve those values.
1) what is the meaning of the file names within the Mapped_Sequence_Reads directory? e.g. file names FC203E3*s_*, FC305JN_s_*, FC30*_s_*, and FC5817_s_* What sort of processing was done on these mapped files eg. masking tags with multiple locations etc.
2) within the Scored_Results directory for STAT1 there are two text files, and another directory (Extended/) containing a text file; what is the functional difference between these files?
3) what are the column headings for the STAT1 mapped files and scored files ?



1. The individual files are the eland aligned reads for each lane of data. Each lane from each flowcell (flowcell IDs are FC203E...) are kept separate even though biological replicate samples were split over multiple lanes. The reads were aligned with the Illumina software Eland with the default settings - only reads where the best alignment (least number of mismatches) is unique in the genome are reported. Reads that align to multiple locations are in the files however the
locations arent reported.
2. In the directory for STAT1 results (http://archive.gersteinlab.org/proj/PeakSeq/Scoring_ChIPSeq/Results/STAT1/STAT1_Targets/) there are two files. STAT1.final.txt contains all the binding site locations sorted by q-value. The other file STAT1.with_peak_locations.txt contains the same information except with one additional field containing the nucleotide position of the peak in each binding site region. I will explain the fields in the file in response to q3. The file in the Extended/ directory contains
all the potential binding site regions (sorted by genomic location) even those that arent enriched relative to the Input DNA control. These two additional files were added at the request of some email I had received.
3. For the mapped files the fields are as follows:
1. Sequence name (derived from file name and line number if format is not Fasta)
2. Sequence
3. Type of match:
NM - no match found.
QC - no matching done: QC failure (too many Ns basically).
RM - no matching done: repeat masked (may be seen if repeatFile.txt was specified).
U0 - Best match found was a unique exact match.
U1 - Best match found was a unique 1-error match.
U2 - Best match found was a unique 2-error match.
R0 - Multiple exact matches found.
R1 - Multiple 1-error matches found, no exact matches.
R2 - Multiple 2-error matches found, no exact or 1-error matches.
4. Number of exact matches found.
5. Number of 1-error matches found.
6. Number of 2-error matches found.
Rest of fields are only seen if a unique best match was found (i.e. the match code in field 3 begins with "U").
7. Genome file in which match was found.
8. Position of match (bases in file are numbered starting at 1).
9. Direction of match (F=forward strand, R=reverse).
10. How N characters in read were interpreted: ("."=not applicable,
"D"=deletion, "I"=insertion).
Rest of fields are only seen in the case of a unique inexact match (i.e. the match code was U1 or U2).
11. Position and type of first substitution error (e.g. 12A: base 12 was A, not whatever is was in read).
12. Position and type of first substitution error, as above.

The fields for the scored files are as follows:
1. chromosome
2. region begin
3. region end
4. tag count from ChIP sample in binding region
5. tag count from control sample in binding region (after normalization)
6. Enrichment (ratio of 4 to 5)
7. Excess tag count (difference between 4 and 5)
8 q-value (Benjamini Hochberg corrected p-value)

Submitting confidential files to Morph Server

I would like to submit two confidential files to the protein Morph Server which contain heteroatoms – the cofactors FAD and NADP+. The server notified me to contact the site maintainers directly for this service. I’d like to calculate 20 frames between the structures.

We have the option of a private site on the submission page (http://molmovdb.org/cgi-bin/submit.cgi). In that case the created web-page won't be added to any databases and won't be searchable. The only person that knows the created link will be able to see it. In case these people won't get email with results they should try manually to open the page http://molmovdb.org/cgi-bin/morph.cgi?ID=given_id where given_id is the ID given at the submission. For example http://molmovdb.org/cgi-bin/morph.cgi?ID=585109-19896

How to reconcile between the Pseudogene Family Database and Eukaryote Database?

I found something misleading that the size of pseudogene protein families database is quite different with the Eukaryote Database. Say,
gene ENSPTRG00000021298, it is contained in Pseudogene Families in Chimp (http://www.pseudogene.org/FAMILY/genome_seq_show.php?genome_ac=9598), but not the Eukaryote Database (http://tables.pseudogene.org/chimp). I wonder whether a gene that has an Ensemble ID is a pseudogene or not.
Which database should I depend on?


For the latest pseudogene families, you may want to take a look of our
Pseudofam database published on NAR recently (http://nar.oxfordjournals.org/cgi/content/abstract/gkn758v1).

However, pseudogene families were built upon the parent proteins of the pseudogenes (which means using Ensembl Peptide/Protein ID rather than Gene ID). Also, pseudogene families only contain pseudogenes that
can be classified into families.

As a result, if you have a set of gene IDs and you wish to see if they have any pseudogenes, I recommend you to download the Chimp's pseudogene set available at Pseudogene.org: http://tables.pseudogene.org/flatfiles/chimp.txt and search for the
gene ID annotation.

For the details of our pseudogene identification, you might want to read our paper published on Bioinformatics previously:
http://bioinformatics.oxfordjournals.org/cgi/content/full/22/12/1437

Huge discrepancy in the numbers in "Modeling ChIP Sequencing in Silico with Applications"

In your article "Modeling ChIP Sequencing in Silico with Applications", you mentioned that the initial 2,915,382 sequence reads obtained in Robertson's experiments, but when I refer this number to the original paper, the total sequenced reads is 24.1M, which is significantlydifferent from your data. Could you clarify, please?

For our ChIP-seq analysis, we used whatever read sequences that Robertson et al sent to us upon our request, which was made well before the publication of their paper.

How do you submit private data to the morph server?

How do you submit private data to the morph server?

There is now a "Private" check box on the morph submission form. If checked, the submitter will still receive an email upon submission but the general public will have no way to find the morph. It will not appear when people use the search box on the front page, nor will it appear among the user-submitted morphs on the movies page. Search engines do not index morph pages since they are dynamically generated. The only way third parties could know of its existence is if they were somehow able to intercept the email sent from the server to the submitter. Thus it is highly unlikely that third parties would ever know of or find it. We trust this will provide sufficient privacy.

I have studied your article "The role of disorder in interaction networks :a structural analysis". I am trying to get a list of hub -party and date- and non-hub proteins, so I am trying to get the datasets you used; however, I cant find the datasets. And so what I am asking for is that is it possible that you guide me to get the dataset somehow?

thank you for your interest in our paper. To answer your question, we employed the datasets provided as supplemental material by Han et al.,
Bertin et al. and Batada et al. Hereafter are the reference of those papers:

• Han JDJ, et al, (2004) Nature 430, 88-93


• Bertin N. et al, (2007) PloS Biol, 5(6):e153


• Batada NN et al. (2007) PloS Biol, 5(6):e154

From Han et al., Supplementary table S1 includes date and party hub information. In our paper, this is referred as FYI 2004. From Bertin et al, we used the filtered-HC Protein-Protein Interaction dataset, provided as Supplementary table S1; called FYI 2007 in our paper.

From the Batada et al. paper, we used the High-Confidence Interaction Dataset provided as Dataset S1 in the Supplementary information . As described in our paper, hubs are then defined as ORFs with more than 10 interacting partners. Finally, to determine which hub is a party or date
hub, we computed the co-expression correlation with their partners. Party hubs have a correlation higher than 0.25 with their interacting partners.

In order to perform the correlation analysis, we employed thecompendium dataset by Huges et al. [ Cell (2000) 102:109-126 ].

Where can I get access to the data driving PubNet?

Where can I get access to the data driving PubNet?

PubNet is based exclusively on PubMed, which you access via query or bulk download from the NCBI.

can you provide an example script for the integrated system for studying residue coevolution in proteins?

Regarding the integrated system for studying residue coevolution in proteins, can you provide an example script that can take one input file in command-line and write result to an output file? Also, can you send me those matlab code for SCA implementation?


The system was implemented in Java. It requires the Java virtual machine, plus some additional packages in order to run locally. If you are interested in installing it on your own machine, I can help sort out the steps. The Matlab code for SCA is unfortunately licensed and we cannot redistribute it. You may contact Rama Ranganathan for it. I think they are also releasing a newer version of SCA.

What is the Protein in the Logo at the Top of the Molmovdb Page?

I've been using your molecular movement database to find candidate proteins for a functionalization experiment that my group at Oregon State University is working on. The logo at the very top of the browsing page caught my attention (http://www.molmovdb.org/images/ProtMotDB.lrg-logo.gif). Would you happen to know what protein this is?

Lactoferrin. It's also part of Figure 4 in the original database publication from a very long time ago:

http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=9722650

This has references to the specific structure publications.

Where is the Source Code for the Dysregulated Pathways cited in "Integrative microarray analysis of pathways dysregulated in metastatic prostate..."?

I came across your paper, "Integrative Microarray Analysis of Pathways Dysregulated in Metastatic Prostrate Cancer". I am having trouble finding an appropriate algorithm to find dysregulated pathways from large clinical expression arrays and was impressed with the method you implemented. I was wondering if you happened to have the source code you used to implement IMAP and if it was possible for me to take a look at it. If so, that would be of enormous assistance to me.

Unfortunately there is no code floating around to perform the analyses you want to do. I did the calculations for the paper you cited but I did them three years ago and the computations were done mostly interactively in an R terminal.

How does one get the corresponding frequencies for the normal modes for which you have generated the movies?

Regarding http://molmovdb.org/nma/, how does one get the corresponding frequencies for the normal modes for which you have generated the movies?

No normal modes are extracted in the process of making the movies

What are the datasetsfor Hinge Atlas and Hinge Gold?

I found the database of your lab is very useful at http://www.molmovdb.org/cgi-bin/browse.cgi, which include many data sets of conformations. My current program can read the pdb files.

Could you send me with the database?




You might find the Hinge Atlas and Hinge Atlas Gold datasets the best curated and easiest to download. You can find the download links and instructions at: http://molmovdb.org/cgi-bin/sets.cgi.

Please cite our Hinge Atlas and/or FlexOracle papers if you use these datasets:

http://papers.gersteinlab.org/e-print/HingeAtlas/preprint.pdf
http://papers.gersteinlab.org/e-print/flexoracle/preprint.pdf

Where is the Data Used for Pseudopiped Paper?

Can you provided me with the data you used for the paper "A computational approach for identifying pseudogenes in the ENCODE region"?


The paper should point to you all the input data, which can be downloaded from the Ensembl website. If you want to know more details about the computational process, you might find them in the following paper too.

http://bioinformatics.oxfordjournals.org/cgi/content/full/22/12/1437

In fact, it might be easy for you to re-produce the computational pipeline described in the above paper.

Is there a program that prints out the coordinates of the grid representing surface?

I recently came across your programs that calculate solvent accessible surfaces. I am interested in a program that would print out the coordinates of the grid representing that surface. The msms program by Senner does something like that but it prints the solvent excluded surface. I briefly looked at your programs but I see that they will only output the surface, but not the grid. I wonder if you have or know where to get such a program?


It will output the entire volume grid if you specify EZD format. Which can be converted to CCP4 and is viewable in UCSF Chimera and PyMol. I would be happy to modify the program to suit your needs, if possible.

If you just want a bunch of points representing the SA surface, my program deals with volumes, not surfaces. The MSMS program outputs coordinates for triangles (texels) representing the surface. My program deals with voxels (3D pixels).

The solvent accessible solvent is actually relatively easy to generate mathematically, the solvent excluded on the other hand is quite tricky. So, if you just want a bunch of points representing the SA surface, I have a perl script that will do that by just creating a bunch of spheres (VDW + probe radius) and then asking whether or not the points are inside another sphere. This works great for SA surfaces, but not SE surfaces.

Human genome build for hg16 Tiling HMM

I read your 2006 paper that describes a supervised hidden markov model framework for tiling array data in transcriptional experiment. In order to gain some insight, the transcriptional experimental data was downloaded from the website. But I wonder what human genome version should the positions in these data be mapped to. I'll appreciate if you could tell me what human genome it is.

hg16 (NCBIv34)

Do you call mutations at key resideus of a protein pseudogenes?

If a gene is transcribed and translated, but there are some mutations at key residues of the protein to make the protein non-functional or very unstable (with very short half life), do we call these kind of gene pseudogene? If it is not, it will be less meaningful for me to classify them, because it is not under the same evolutional pressure as functional genes. If it is, computer algorithms may have difficulty to identify them.

This is a very interesting question. The definition of "gene" and "pseudogene" is extremely fuzzy. Currently, our pipeline will not call this a pseudogene because we primarily look for frame-shifts and nonsense mutations. We can identify processed pseudogenes which don't have frame-shifts or nonsense mutaions, specifically pseudogenes of multiexon genes that will appear as a single exon retrotransposed gene. We don't have a clear way of differentiating between a functional retrogene and pseudogene. We simply flag it is a processed pseudogene. If the gene of interest has many exons and this structure is retained in the non-functional entities, we will not call it a pseudogene unless we detect a frame-shift or a nonsense mutation. But we are constantly adding new features to our pipeline and will have a discussion with Prof. Gerstein and the rest of the team about this aspect.

How good is Pseudogene Identification?

How good is the current algorithm to identify pseudogenes? For the maiz example, how can we know that thousands of copies of RVP genes on transoposons are functional or not?

1. Our pipeline has specific criteria for identifying pseudogenes and the first step involves filtering out exons annotated as protein coding. Therefore, if the underlying genome annotation is incorrect, then we will miss some pseudogenes. The scenario you have described is similar to ribosomal protein pseudogenes where we observe several retrotransposed pseudogenes. In this case, we specifically modified the pipeline to not mask the exons as most of the ribosomal proteins were misannotated in databases.

2. I am not very familiar with work on maize genome or pseudogenes in plants. I will discuss more with my colleagues and get back to you if there are new insights. But based on my experience with ribosomal protein pseudogenes, most such processed pseudogenes are non-functional. While one can never be sure if something is non-functional, there are a few things that one could do

a. Compare multiple genomes at various distances to maize genome to see if that region is conserved. If it is, there is some biological preference for retaining those pseudogenes.

b. Look to see if there are known promoter elements upstream of these regiosn which could potentially enable transcription/translation.

You might want to refer to a paper we recently published on ribosomal protein pseudogenes,Comparative analysis of processed ribosomal protein pseudogenes in four mammalian genomes

How do I get data for the Bayesian Networks Paper?

I am a graduate student in University of Science and Technology of China majoring in bioinformatics. I am to perform some experiment concerning PPI network, and i found your article A Bayesian networks approach for predicting protein-protein interactions from genomic data very useful to my work, and need the variousdatasets preprocessed by your group. Will you send me a copy or tell me the site where i can download the data?


You could find the data from the supplementary website:http://networks.gersteinlab.org/intint/supplementary.htm

How to obtain Standalone version of Calc-surface?

I am wondering if I could get a stand-alone version of calc-surface programe, I cannot find it in the software page of Prof. Gerstein lab.

I don't release binaries, because I am not good enough at it, to make it compatible with most systems. I would be happy to compile it for you, but I need to know what type of system you have: Linux, Mac, 32bit, 64bit, G4, G5. I am sorry to say I can't do Windows. Please contact the lab

How do I modify source code of Calc-Surface?

I want to use calc-surface with a large probe of 14 Angstroms but calc-surface seg faults when the probe is larger than 3 to 4 Å. I would like to modify the code to handler larger probes, can you point me in the right direction as to where to edit the code? I am using version 2.3.1.


The code you should be editing is called calc-surface.main.c which is in:

libproteingeometry-2.3.1/src-prog

I would also be careful about some other scripts or sub-routines that this program calls. Most of the scripts are usually in the same dir. All the programs are in one of these three:
src-prog, src-pro2 and src-pro3.