Search results for: Connectivity map
Matching directly transcriptional signatures of a disease with negatively correlated transcriptional signatures of chemical perturbations (CP) underlies the Connectivity Map (CMap) approach to identifying potential drug candidates. Similarly, correlating signatures of chemical perturbagens with genetic perturbations of specific genes has been used to identify putative targets of drugs and other...
Transcriptional signatures of perturbagen activity constructed based on the version 2 of the original Connectivity Map dataset using Affymetrix expression arrays. Each signature consists of differential expressions and associated p-values for all genes when comparing perturbagen treated cell lines with appropriate controls.
216,105 transcriptional signatures of cellular perturbations constructed using the LINCS pilot phase L1000. The chemical perturbagen and individual shRNA signatures are created by aggregating (ie averaging) Level 4 data for biological replicates as defined by the signatures metadata. Only signatures designated to be reproducible and self-connected ("gold") by the Broad institute are represented...
In the "Signatures" pipeline, you may explore, analyze and visualize over 200,000 pre-computed signatures (i.e. list of "scores" (activity levels) for a list of genes or for all genes in the genome "genome-wide signatures"). One would land on the Signatures landing page by clicking "Signatures" on the iLINCS portal header.
As shown in the figure above, there are 9 pre-computed signature libraries...
iLINCS (Integrative LINCS) is an integrative web platform for analysis of LINCS data and signatures. The portal provides biologists-friendly user interfaces for analyzing transcriptomics and proteomics LINCS datasets. The portal integrates R analytical engine via several R tools for web-computing (rserve, opencpu, Shiny, rgl) and DCIC developed web tools and applications (FTreeView, Enrichr) into...
The perturbagen connectivity analysis compares the query signature to all signatures
for a given perturbagen as a group, thus extending the pair-wise connectivity analysis
to account for diversity of responses in different cellular contexts. This
is accomplished by performing the enrichment analysis of individual connectivity
scores between the query signature and set of all L1000 signatures of a...
PiNET can be used to annotate, map and analyze a set of peptide moieties (including post-translationally modified peptides) identified by either targeted (SRM type) or SWATH (discovery) proteomic assays, or another related mass spectrometry based protein moieties identification and quantification technique. (http://pinet-server.org)
Depending on the exact type of the query signature, the connectivity analysis with libraries of
pre‐computed iLINCS signature are computed using different connectivity metric.
If the query signature is selected from iLINCS libraries of pre‐computed signatures, the
connectivity with all other iLINCS signatures is pre‐computed using the extreme Pearson’s
correlation signed significances of all...
RNA-seq is a Next Generation Sequencing platform that measures gene expression across the transcriptome. A population of RNA (total or fractionated, such as poly(A)+) is converted to a library of cDNA fragments with adaptors attached to one or both ends. Each molecule is then sequenced in a high-throughput manner to obtain short sequences from one end (single-end sequencing) or both ends (pair-end...
1. One may be interested to see all the metadata available for a particular precomputed signature. Let's say we would like to see more information for "LINCSCP_131839" signature. Let's click on the signature title as shown in the figure below.
2. As seen in the figure below, clicking on the signature title, opens up a new window containing a landing page for that particular signature. Similar...
iLINCS pre-calculated signature connectivity is based on extreme correlation analysis, on the other hand, the uploaded signatures' similarity is based on weighted correlation calculation, please see the method section (https://www.nature.com/articles/s41467-022-32205-3).
In the following example, we will start with a gene knockdown (loss-of-function) transcriptional signature and will try to identify a drug or sets of drugs that have opposite transcriptional signatures. For this example, we will look at MTOR gene knockdown in PC3, prostate cancer cells; will compare its transcriptional signature to the known MTOR inhibitor drug, Sirolimus (Rapamycin) signature and...
In the following example, we will try to identify a signature(s) that would reverse activated Estrogen receptor transcriptional signature profile. First, we will select Estradiol treatment perturbagen signature in MCF7 (ER+ breast cancer cell line) and then will identify highly disconnected (opposite) signature(s) to reverse its transcriptional signature profile via either gene loss-of-function...
Citation: Connecting omics signatures of diseases, drugs, and mechanisms of actions with iLINCS
Marcin Pilarczyk, Mehdi Fazel-Najafabadi, Michal Kouril, Behrouz Shamsaei, Juozas Vasiliauskas, Wen Niu, Naim Mahi, Lixia Zhang, Nicholas A. Clark, Yan Ren, Shana White, Rashid Karim, Huan Xu, Jacek Biesiada, Mark F. Bennett, Sarah E. Davidson, John F. Reichard, Kurt Roberts, Vasileios Stathias, Amar...
Global Chromatin Profiling (GCP) technology is a mass spectrometry-based assay to identify and quantify post-translational modifications on histone proteins from bulk chromatin (i.e. measuring changes in epigenetic marks on histones). Around 60 different combinations of histone modifications can be quantified on H3, with even more possible combinations on H4, H2A (including isoforms), and H2B...
Transcriptional signatures of gene overexpression based on L1000 assay. The signatures consist of differential gene expressions and p-values for 978 Landmark Genes measured by L1000 assay. The signatures were created by aggregating (ie averaging) Level 4 data for biological replicates as defined by the signatures metadata. Only signatures designated to be reproducible and self-connected ("gold...
Transcriptional signatures of perturbations by small molecules based on L1000 assay. Signatures were created by aggregating (ie averaging) Level 4 data for biological replicates as defined by the signatures metadata. Only signatures designated to be reproducible and self-connected ("gold") by the Broad institute are represented. The signatures consist of differential gene expressions and p-values...
1. Search is a very important part of this portal given that the number of LINCS datasets and precomputed signatures is constantly growing. One is able to search for a LINCS dataset and/or precomputed signature of interest on iLINCS portal in a couple of ways. In the example below, we will search for a precomputed signatures for MCF7 cell line (the example of locating LINCS dataset of interest is...
In the following work-flow example, we will start with a prototypical drug and will identify sets of drugs that have similar transcriptional signatures. Moreover, we will also pinpoint genes and pathways that are affected by the drug.
1. First, let's open Signatures Pipeline starting with the iLINCS homepage as shown below.
2. This will take you to a Signatures pipeline landing page that lists...